Biomarkers for non-hodgkin lymphomas and uses thereof

ABSTRACT

The disclosure provides a method of identifying a subject as having B-cell non-Hodgkin lymphoma (NHL) such as testing a sample from a subject for a mutation in one or more biomarkers. Also described are methods for classifying or monitoring a subject having, or suspected of having, B-cell non-Hodgkin lymphoma comprising testing the sample for a mutation in one or more biomarkers.

RELATED APPLICATIONS

This is a Patent Cooperation Treaty Application which claims the benefitof 35 U.S.C. 119 based on the priority of corresponding U.S. ProvisionalPatent Application No. 61/357,813 filed Jun. 23, 2010, and U.S.Provisional Application No. 61/420,065 filed Dec. 6, 2010, the contentsof which are incorporated herein in their entirety.

FIELD OF THE DISCLOSURE

The disclosure relates to methods of testing for cancer and morespecifically to methods of testing samples for somatic mutationsindicative of B-cell Non-Hodgkin Lymphomas (NHLs).

BACKGROUND OF THE DISCLOSURE

Non-Hodgkin lymphomas (NHLs) are cancers of B, T or natural killerlymphocytes. The two most common types of NHL, follicular lymphoma (FL)and diffuse large B-cell lymphoma (DLBCL), together comprise 60% of newB-cell NHL diagnoses each year in North America [1]. FL is an indolentand typically incurable disease characterized by clinical and geneticheterogeneity. DLBCL is aggressive and likewise heterogeneous,comprising at least two distinct subtypes that respond differently tostandard treatments. Both FL and the germinal centre B-cell (GCB) cellof origin (COO) subtype of DLBCL derive from germinal centre B cellswhereas the activated B-cell (ABC) variety, which exhibits a moreaggressive clinical course, is thought to originate from B cells thathave exited, or are poised to exit, the germinal centre [2]. Currentknowledge of the specific genetic events leading to DLBCL and FL islimited to the presence of a few recurrent genetic abnormalities [2].For example, 85-90% of FL and 30-40% of GCB DLBCL cases [3, 4] harbourt(14;18)(q32;q21), which results in deregulated expression of the BCL2oncoprotein. Other genetic abnormalities unique to GCB DLBCL includeamplification of the c-REL gene and of the miR-17-92 microRNA cluster[5]. In contrast to GCB cases, 24% of ABC DLBCLs harbour structuralalterations or inactivating mutations affecting PRDM1, which is involvedin differentiation of GCB cells into antibody-secreting plasma cells[6]. ABC-specific mutations also affect genes regulating NF-κBsignalling [7-9], with TNFAIP3 (A20) and MYD88 [10] the most abundantlymutated in 24% and 39% of cases respectively.

Despite the disparity in response to therapy of the individual subtypesand the knowledge of clear genetic differences between the subtypes,clearly identifying B-cell NHLs remains challenging. Accordingly, thereis a need for improved methods of identifying as well as classifyingB-cell NHLs including GCB and ABC DLBCLs.

SUMMARY OF THE DISCLOSURE

In one aspect, the present disclosure is directed towards new and usefulmethods for the identification and/or classification of B-cell NHLs. Asdescribed herein, the inventors have (1) identified somatic mutationsand (2) determined the prevalence, expression and focal recurrence ofmutations in follicular lymphoma (FL) and diffuse large B-cell lymphoma(DLBCL) in order clarify the genetic architecture of B-cell NHLs. Usingstrategies and techniques applied to cancer genome and transcriptomecharacterization [11-13], tumour DNA and/or RNA was sequenced from 117tumour samples and 10 cell lines and 651 genes were identified withevidence of somatic mutation in B-cell NHL. After validation, 109 geneswere shown to be somatically mutated in 2 or more NHL cases. Thefrequency and nature of mutations within MLL2 and MEF2B, which wereamong the most frequently mutated genes with no previously known role inlymphoma are also described herein.

As set out in Example 1, a number of biomarkers useful for identifyingsamples with B-cell NHL have been identified. More specifically, thebiomarkers listed in Table 1 have been confirmed as somatic mutations intumour samples from subjects with B-Cell NHL and show significantevidence for positive selection. In another aspect of the disclosure, anumber of biomarkers useful for classifying samples into subtypes ofB-cell NHLs have been identified. Some biomarkers have been shown to beselectively mutated in either germinal centre B-cell (GCB) Diffuse LargeB-cell Lymphoma (DLBCL) or Activated B-Cell (ABC) DLBCL and aretherefore useful for classifying samples as belonging to either the GCBor ABC subtype of DLBCL. Thus, application of the methods describedherein allows for the identification of those subjects with specificsubtypes of B-cell NHL and enable improved disease management andpharmacological treatment with agents best suited to a particulardisease subtype.

Remarkably, a number of the biomarkers associated with B-cell NHLsdescribed herein are involved in histone modification. Morespecifically, the inventors have discovered that at least fivebiomarkers (MLL2, MEF2B, CREBBP, EP300, EZH2 and HDAC7) shown to beselectively mutated in B-cell NHLs are predicted to be involved in theprocess of histone modification. Post-translational modifications ofhistones, such as methylation and acetylation, can affect theaccessibility of stretches of genomic DNA to transcription factors.Mutations in MLL2 are predicted to affect levels of histone methylationwhile mutations in MEF2B are predicted to affect histone acetylation.Moreover, mutations in MEF2B are predicted to affect the ability ofMEF2B to regulate acetylation levels via these three enzymes (HDAC7,CREBBP and EP300). Testing a sample for mutations in histone modifyinggenes is therefore useful for the identification of B-cell NHLs.

Accordingly, in one aspect there is provided a method of identifying asubject as having B-cell non-Hodgkin lymphoma (NHL), the methodcomprising testing a sample from the subject for a mutation in one ormore biomarkers listed in Table 1. In one embodiment, the presence of amutation in the sample identifies the subject as having B-cell NHL. Inone embodiment, the method comprises detecting one or more mutations ina nucleic acid molecule coding for a biomarker. In one embodiment, themethod comprises detecting one or more mutations in a polypeptide orprotein coding for a biomarker. In one embodiment, the method comprisesdetecting mutations in one or more histone modifying genes such as MLL2,MEF2B, CREBBP, EP300, EZH2 or HDAC7. In one embodiment, the biomarkersare selected from FOX01, CCND3, BTG2, B2M, TNFRS14, CREBBP, EP300,BCL10, BTG1, GNA13, SGK1, MLL2, MEF2B, CD79B and MYD88. Optionally, 2 ormore, 3 or more, 4 or more, 5 or more or greater than 5 of thebiomarkers listed in Table 1 or described herein are tested formutations. The methods described herein also include testing the samplefor one or more of the mutations described herein such as those listedin Table 3, Table 5, Table 6, Table 7 or Table 9. In one embodiment, thebiomarker is MEF2B and the method comprises detecting a mutation in anucleic acid molecule or polypeptide corresponding to a mutation atamino acid position K4, Y69, N81 or D83 of the MEF2B polypeptide.

In another aspect of the disclosure, there is provided a method ofclassifying a subject suspected of having, or having, B-cell non-Hodgkinlymphoma (NHL). In one embodiment, the method comprises testing a samplefrom the subject for a mutation in one or more biomarkers selected fromMEF2B, SGK1, GNA13, and TNFRS14. In one embodiment, samples that haveone or more mutations in one or more biomarkers selected from MEF2B,SGK1, GNA13, and TNFRS14 are classified as having germinal centre B-cell(GCB) Diffuse Large B cell lymphoma (DLBCL). Optionally, the methodfurther comprises testing the sample for a mutation in BCL2, TP53 orEZH2.

In one aspect of the disclosure, there is provided a method ofclassifying a subject suspected of having, or having, B-cell non-Hodgkinlymphoma (NHL) comprising testing the sample for one or more mutationsin MYD88 or CD79B. In one embodiment, samples that have a mutation inMYD88 or CD79B are classified as having activated B-cell (ABC) DiffuseLarge B cell lymphoma. Optionally, the method for classifying a subjectsuspected of having, or having, B-cell non-Hodgkin lymphoma (NHL)includes testing for one or more of MEF2B, SGK1, GNA13, TNFRS14, MYD88or CD79B.

The methods described herein are also useful for classifying a subjectin order to select a suitable treatment for the subject. In oneembodiment, the methods include selecting a treatment for a subjectbased on the classification of the sample as GCB DLBCL or ABC DLBCL. Forexample, in one embodiment the sample is classified as GCB DLBCL, and atreatment is selected that comprises administration of a histonedeacetylase (HDAC) inhibitor-class drug. In one embodiment, the methodsfor classifying a subject described herein comprise testing a samplefrom the subject for one or more of the mutations listed in Table 3,Table 5, Table 6, Table 7 or Table 9.

In another aspect of the disclosure, there is provided a method ofmonitoring a subject with B cell non-Hodgkin lymphoma (NHL) comprisingtesting a first sample from the subject for a mutation in one or morebiomarkers listed in Table 1 and comparing the results to a control.Optionally, the control represents results from testing a second sampletaken from the subject at an earlier time point. In one embodiment, themethod comprises testing one or more biomarkers selected from MLL2,MEF2B, CREBBP, EP300, EZH2, H3K27, FOX01, CCND3, BTG2, B2M, TNFRS14,BCL10, BTG1, GNA13, SGK1, MYD88 and CD79B. In one embodiment, the methodcomprises testing for one or more of the mutations listed in Table 3,Table 5, Table 6, Table 7 or Table 9.

Other features and advantages of the present disclosure will becomeapparent from the following detailed description. It should beunderstood, however, that the detailed description and the specificexamples while indicating preferred embodiments of the disclosure aregiven by way of illustration only, since various changes andmodifications within the spirit and scope of the disclosure will becomeapparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the present disclosure will now be describedin relation to the drawings in which:

FIG. 1 shows a genome-wide visualization of somatic mutation targets inNHL. Overview of structural rearrangements and copy number variations(CNVs) in the 11 DLBCL genomes and protein-altering single nucleotidevariants (coding SNVs; cSNVs) in the 109 recurrently mutated genesidentified in our analysis. Inner arcs represent somatic fusiontranscripts identified in one of the 11 genomes. The CNVs (copy numbervariants) and LOH (loss of heterozygosity) detected in each of the 11DLBCL tumour/normal pairs are displayed on the concentric sets of rings.The inner 11 rings show regions of enhanced homozygosity plotted withblue (interpreted as LOH). The outer 11 rings show somatic CNVs. Purplecircles indicate the position of genes with at least two confirmedsomatic mutations with circle diameter proportional to the number ofcases with cSNVs detected in that gene. Circles representing the geneswith significant evidence for positive selection are labeled.Coincidence between recurrently mutated genes and regions of gain/lossare colour-coded in the labels (green=loss, red=gain). For example B2M,which encodes beta-2-microglobulin, is recurrently mutated and isdeleted in two cases.

FIG. 2 shows an overview of mutations and potential cooperativeinteractions in NHL. This heat map displays possible trends towardsco-occurrence (red) and mutual exclusion (blue) of somatic mutations andstructural rearrangements. Colours were assigned by taking the minimumvalue of a left- and right-tailed Fisher exact test. To capture trends aP-value threshold of 0.3 was used, with the darkest shade indicatingthose meeting statistical significance (P<=0.05). The relative frequencyof mutations in ABC (dark grey), GCB (darkest grey), unclassifiable(light grey) DLBCLs and FL (lightest grey) cases is shown on the left.Genes were arranged with those having significant (P<0.05, Fisher exacttest) enrichment for mutations in ABC cases (dark grey triangle) towardsthe top (and left) and those with significant enrichment for mutationsin GCB cases (darkest grey triangle) towards the bottom (and right). Thetotal number of cases in which each gene contained either cSNVs orconfirmed somatic mutations is shown at the top. The cluster of squares(upper-right) results from the mutual exclusion of the ABC-enrichedmutations (e.g. MYD88, CD79B) from the GCB-enriched mutations (e.g.EZH2, GNA13, MEF2B, SGK1). Presence of structural rearrangementsinvolving the two oncogenes BCL6 and BCL2 (indicated as BCL6s and BCL2s)was determined with FISH techniques utilizing break-apart probes.

FIG. 3 shows a summary and effect of somatic mutations affecting MLL2and MEF2B. (A) Re-sequencing the MLL2 locus in 89 samples revealedmainly nonsense (dark grey circles) and frameshift-inducing indelmutations (triangles). A smaller number of non-synonymous somaticmutations (light grey circles) and point mutations or deletionsaffecting splice sites (stars) were also observed. All of thenon-synonymous point mutations affected a residue within either thecatalytic SET domain, the FYRC domain (“FY-rich C-terminal domain”) orPHD zinc finger domains. The effect of these splice site mutations onMLL2 splicing was also explored. (B) The cSNVs and somatic mutationsfound in MEF2B in all FL and DLBCL cases sequenced are shown with thesame symbols. Only the amino acids with variants in at least twopatients are labelled. cSNVs were most prevalent in the first twoprotein coding exons of MEF2B (exons 2 and 3). The crystal structure ofMEF2 bound to EP300 supports that two of the four hot spots (N67 andY69) are important in the interaction between these proteins [50].

FIG. 4 shows the N-terminal truncation of FOXO1 protein with mutationaffecting initial codon. (A) The RNA-seq data of cell lines and patientsamples revealed mutations in 3 samples affecting the initial codon ofFOXO1. To determine the effect of such mutations on FOXO1 protein, weassayed FOXO1 by Western blot in DLBCL cell lines using an antibodyraised against full-length FOXO1 (2H8.2). In the cell line containing amutation at the initiator methionine (OCI-Ly1), we observed a FOXO1 bandof reduced molecular weight, compared to FOXO1 wild-type cell lines(size indicated in Kilodaltons on the left). The reduced size isconsistent with the use of a second methionine codon in the FOXO1 gene,producing a protein shortened at the amino terminus by 70 amino acids.The same blot was also probed with an antibody that recognizes anN-terminal epitope (L27) and lack of a band in OCI-Ly1 cells isconsistent with the notion that the lower band in this cell linecorresponds to FOXO1 protein lacking its N-terminus. Absence of theprotein in the DB cell line was noted, which showed significantlyreduced mRNA levels as measured by RNA-seq (upper bar chart; RPKM=ReadsPer Kilobase of gene model per Million mapped reads).

FIG. 5 shows the effect of GNA13 mutations at the protein level. (A) Awestern blot revealed the expected lack of GNA13 protein in DOHH2, thecell line with a truncating point mutation detected in the RNA-seq data.The lack of protein in Karpas422, SU-DHL-6 and WSU-DLCL2 was surprising,as protein-truncating mutations were not detected in these cells. (B)Further analysis of the aligned sequence from these three cell lines andadditional analysis utilizing a de-novo transcript assembly approach(Trans-ABySS; Methods), revealed multiple aberrations that may explainthe lack of protein. Firstly, in Karpas422 reads were observed to mapthe first intron, suggesting that the intron is retained in asignificant proportion of GNA13 transcripts (compare Karpas422 on theleft to WSU-DLCL2 on the right). Inspection of sequence contigs fromthis case revealed the likely cause of intron reads to be a deletion of87 nt that removes the canonical splicing donor from this exon (Panel C,top). Splicing still appears to occur to a lesser extent using a non-GTdonor. Assembled reads from SU-DHL-6 revealed a 2 nt deletion and alarge 1028 nt deletion. The former would affect the reading frame andthe latter removes the terminal stop codon. Finally, in WSU-DLCL2, thesplicing donor after the third exon was apparently mutated, convertingthe GT donor to a GC sequence (not shown). As in the Karpas422 case,there was clear evidence for retention of this intron in GNA13transcripts in WSU-DLCL2. Intron retention has previously been linked tononsense-mediated transcript degradation [76] and if that is the casehere, could explain the lack of GNA13 protein in these cells.

FIG. 6 shows the predicted impact of recurrently mutated genes on BCRsignalling and downstream messengers. (A) Autocrine and paracrinestimulation of IL-21R induces the dimerization and activation of STAT3,a positive regulator of PRDM1 expression [77]. Mutations affecting theDNA binding domain of STAT3 are known to act as dominant negatives,which would predict the inability to induce PRDM1 expression followingIL-21 stimulation. (B) Multiple mutations predicted to directly alterBCR signalling or alter the normal events subsequent to BCR-inducedinflux of the secondary messenger Ca²⁺ Cross-linking of CD58 has beenshown to result in the phosphorylation of BLNK, Syk and PLC-gamma andlead to Akt activation [78]. Various mutations are expected to alter theability of B cells to induce the expression of MEF2 target genes inresponse to the Ca²⁺ influx. The role of MEF2 gene family members inmediating epigenetic alterations downstream of the BCR has been inferredfrom a knockout study in which MEF2C was shown to be required formediating calcium-dependent response to BCR signaling [79] and theinvolvement of CREBBP/EP300 in this process has been inferred fromMEF2-mediated transcriptional regulation in other cell types including Tcells [80]. This model predicts that influx of Ca²⁺ after BCRstimulation would result in the displacement of HATs by activatedCalmodulin-dependent protein kinase (CAMK), allowing HDAC activity viaCREBBP/EP300 thus enabling transcription at MEF2 target loci. In thismodel, mutation of any of these three genes and potentially the S155Fmutation in HDAC7 would diminish this effect and suppress the inductionof MEF2 target loci after BCR stimulation. (C) Multiple mutations mayaffect the regulation of the activity of FOXO proteins following BCRstimulation. FOXO1 is a downstream target of the kinase AKT, which isactivated during BCR signalling. SGK, a related kinase (mutated inB-cell NHLs as described herein), is known to phosphorylate FOXO3a in asimilar way [25] and the present applicants predict it to alsophosphorylate FOXO1. Thus, mutations affecting the FOXO1 phosphorylationsite or SGK1 could affect the regulation of FOXO1 nuclear localizationand hence, its transactivation activity. The shortened FOXO1 proteinproduced by mutation of the initial codon (FIG. 4) would not containthis phosphorylation site and hence those mutations may also result inaltered subcellular localization. Various mutations affecting NF-κBactivity, which have been previously described, were also observed here[9-10, 18, 21]. (D) Many of the recurrently mutated genes in B-NHL areinvolved in histone modification or themselves encode histone proteins(i.e. HIST1H1C, one of multiple genes that encode histone protein H1).CREBBP/EP300 and MLL2 each produce activating chromatin marks (H3K27Acand H3K4me3, respectively). HDAC (e.g. HDAC7) and EZH2 produceinactivating marks by removing acetyl groups and trimethylating H3K27,respectively. As heterozygous EZH2 Y641 mutations are known toeffectively enhance PRC2 activity [43], then each of the individualmutations may result in suppression of gene expression. It have not beenconfirmed whether EZH2 and MLL2 regulate the expression of the samegenes as MEF2B/CREBBP/EP300.

DETAILED DESCRIPTION OF THE DISCLOSURE I. Definitions

As used herein, “B-cell Non-Hodgkin Lymphoma” or “B-cell NHL” refers toany lymphoma of B-cells except those classified as Hodgkin lymphoma. Asused herein, “lymphoma” refers to a cancer in the lymphatic cells of theimmune system.

As used herein, “follicular lymphoma” or “FL” refers to a lymphoma offollicle center B-cells (centrocytes and centroblasts), which has atleast a partially follicular pattern.

As used herein, “Diffuse Large B cell lymphoma” or “DLBCL” refers to alymphoma of B-cells wherein the cells are generally about 4-5 times thediameter of small lymphocytes and typically have marked cell-to-cellvariation in size and shape. Typically, their cytoplasm is basophilicand moderate in abundance. Nucleoli can be small but conspicuous tolarge and prominent and may be peripheral and/or central.

As used herein “germinal centre B-cell lymphoma” or “GCB lymphoma”refers to a subtype of DLBCL wherein the lymphoma appears to arise fromgerminal centre B cells. Typically, GCB cells have a pattern of geneticexpression that is similar to germinal center B cells and often achromosomal translocation involving the gene bcl-2.

As used herein “activated B-Cell lymphoma” or “ABC lymphoma” refers to asubtype of DLBCL wherein the lymphoma appears to arise from postgerminalcentre B cells that are arrested during plasmacytic differentiation.

The term “biomarker” as used herein can be any type of moleculecorresponding to a gene listed in Table 1, or any type of moleculeidentified herein which can be used to distinguish samples with orwithout B-cell NHL or between subtypes of B-cell NHL. The term biomarkerincludes without limitation, a nucleic acid sequence including a gene,or corresponding RNA or cDNA, or a polypeptide, fragment thereof, orepitope that is differentially present, including differentiallymodified (e.g. differentially glycosylated), expressed, and/or solublebiomarkers e.g. biomarkers which are detectable in a biological fluidand which are differentially cleaved, secreted, released or shed insubjects with or without B-cell NHL. In one embodiment, detecting one ormore mutations in one or more biomarkers in a sample from a subjectindicates that the subject has B-cell NHL.

As used herein, the term “sample” refers to any biological fluid, cellor tissue sample from a subject which can be assayed for biomarkers(e.g. DNA, RNA and/or polypeptide products), such as soluble biomarkersin subjects having or not having B-cell NHL. Optionally, the samplecomprises nucleic acids and/or proteins that have been isolated,purified or otherwise treated. For example, a sample may be fractionated(e.g. by centrifugation or using a column for size exclusion),concentrated or proteolytically processed such as trypsinized, dependingon the method of testing for mutations in the biomarker employed. Thesample may be a biological fluid such as blood, serum, saliva,cerebrospinal fluid, plasma, or lymphatic fluid, a tissue sample ortissue biopsy. In one embodiment, the sample is a “tumour sample”. Asused herein “tumour sample” refers to a sample of cells from a subjectthat is undergoing uncontrolled cell division. In a preferredembodiment, the sample comprises all or part of one or more lymphoidcells, lymph nodes or a lymph node biopsy. In another preferredembodiment, the sample is a blood sample or plasma sample.

As used herein, the term “subject” refers to any member of the animalkingdom, and includes mammals such as humans. The term also includessubjects having cancer or suspected of having cancer, such as B-cellNHL. Optionally, the subject is symptomatic or asymptomatic of B-cellNHL.

As used herein the phrase “subject suspected of having B-cellnon-Hodgkin lymphoma” refers to a subject for which informationregarding whether or not the subject has B-cell NHL or a particularsubtype of B-cell NHL is desired. Optionally, a subject suspected ofhaving B-cell NHL may present with one or more symptoms such as:swollen, painless lymph nodes in the neck, armpits, or groin; suddenweight loss; coughing, trouble breathing, or chest pain; and/or pain orswelling in the abdomen.

As used herein “mutation” refers to a variant of biomarker that does notappear in a control sample that alters the presence, amount orbiological activity of a biomarker as described herein. In oneembodiment the control sample is from a subject that does not haveB-cell NHL or from a sample that is not undergoing uncontrolled celldivision. In one embodiment, the control sample is from the same subjectas the test subject but is taken at a different point in time. In oneembodiment, the mutation is a variant of the wild-type nucleic acidsequence or polypeptide sequence for that biomarker. In one embodiment,the mutation is a nonsense mutation, non-synonymous mutation, insertionor deletion. In one embodiment, the mutation is not known prior totesting the sample for a mutation. In one embodiment, the mutation is acoding Single Nucleotide Variant (cSNV). In one embodiment, the mutationis a copy number variant (CNV) or loss of heterozygozity (LOH). As usedherein, the term “somatic mutation” refers to a mutation that isacquired after the formation of a zygote and is not found in themajority of cells in a subject. Examples of mutations include thoselisted herein in Tables 3, 5, 6, 7 and 9.

As used herein “testing a sample from the subject for a mutation” refersto analyzing the sample to determine the presence or absence of amutation in a biomarker. In one embodiment, testing the sample for amutation involves sequencing nucleic acid molecules that encode thebiomarker or part of the biomarker. In another embodiment, testing thesample for a mutation involves detecting a mutant polypeptide such as byprotein sequencing, use of selective antibodies, or the use of massspectrometry based genotyping assays.

As used herein, “classifying a subject as having germinal centre B-celllymphoma” refers to identifying the subject as being more likely to havegerminal centre B-cell lymphoma than other types of B-cell NHL. In oneembodiment, a subject classified as having GCB lymphoma is excluded fromhaving ABC lymphoma.

As used herein, “classifying a subject as having activated B-celllymphoma” refers to identifying the subject as being more likely to haveActivated B-cell lymphoma than other types of B-cell NHL. In oneembodiment, a subject classified as having ACB lymphoma is excluded fromhaving GCB lymphoma.

As used herein “selecting a treatment” refers to determining a course oftherapeutic action for a subject from a plurality of possible treatmentoptions. For example, “selecting a treatment” may comprise selecting aspecific pharmaceutical agent for administration to a subject withB-cell NHL in need thereof, as opposed to another pharmaceutical agentwhich may be ineffective for a particular subtype of B-cell NHL.Clinical trials that test the selective activity of therapies in ABCDLBCL are ongoing. These include the utility of drugs that reduce theactivity of the transcription factor NFkB, thus reducing expression ofNFkB target genes. Such drugs include Bortezomib and Lenalidomide [100;101].

As used herein, “monitoring a subject with B-cell non Hodgkin lymphoma”refers to ascertaining the progression or remission of the B-cell NHL ina subject over time.

II. Methods Methods for Identifying B-Cell NHLs

The present disclosure pertains to methods for detecting B-cell NHLsusing biomarkers that have been shown to be mutated in samples fromsubjects with B-Cell NHL. As set out in Example 1, the biomarkersidentified in Table 1 have been shown to be mutated in at least 2 ormore cases of NHL and furthermore exhibit evidence for positiveselection with either selective pressure for acquiring non-synonymouspoint mutations or truncating/nonsense mutations.

Accordingly, in one embodiment, there is provided a method ofidentifying a subject as having B-cell non-Hodgkin lymphoma comprisingtesting a sample from the subject for a mutation in one or morebiomarkers listed in Table 1. A variety of methods known in the art maybe used to test the sample to identify mutations in the biomarkers. Forexample, mutations may be detected in a nucleic acid molecule such asgenomic DNA or mRNA. Alternatively, mutations may be detected in apolypeptide that corresponds to a biomarker listed in Table 1. In oneembodiment, the mutation is listed in Tables 3, 5, 6, 7 or 9. In apreferred embodiment, the sample is tested for mutations by sequencingDNA coding for the biomarker. Optionally, the method involves amplifyingthe nucleic acid coding for the biomarker using PCR.

Various methods or techniques for identifying mutations in nucleic acidmolecules that known in the art may be used in order to detect mutationsin the biomarkers described herein. For example, embodiments include,but are not limited to, techniques such as primer extension, classicalmicroarrays, sequencing or line probes. Methods of PCR product endpointdetection including, but not limited to, fluorescence,chemiluminescence, colourimetric techniques or measurement of redoxpotential may also be used with the embodiments described herein fordetecting mutations in nucleic acid sequences. Optionally, the relativeor absolute amount of a nucleic acid molecule corresponding to abiomarker is determined and compared to a control sample.

In another embodiment, various methods or techniques for identifyingmutations in polypeptides that are known in the art may be used in orderto detect mutations in the biomarkers described herein. For example,methods useful for detecting a mutation in a polypeptide correspondingto a biomarker as described herein, include mass spectrometryapproaches, such as multiple reaction monitoring (MRM) and product-ionmonitoring (PIM), and immunoassays such as Western blots, enzyme-linkedimmunosorbant assays (ELISA), and immunoprecipitation followed bysodium-dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)immunocytochemistry and protein sequencing methods.

In one embodiment, antibodies or antibody fragments are used to detect apolypeptide of one or more biomarkers of the disclosure or the mutatedforms a polypeptide of one or more biomarkers of the disclosure.Antibodies having specificity for a specific polypeptide, or a specificmutated polypeptide, such as the protein product of a biomarker gene ofthe disclosure, may be prepared by conventional methods. In anembodiment, the antibody or antibody fragment is labeled with adetectable marker. In a further embodiment, the antibody or antibodyfragment is, or is derived from, a monoclonal antibody. A person skilledin the art will be familiar with the procedure for detecting the apolypeptide biomarker by using said antibodies or antibody fragments,for example, by contacting the sample from the subject with an antibodyor antibody fragment labeled with a detectable marker, wherein saidantibody or antibody fragment forms a complex with the biomarker.Optionally, the relative or absolute amount of a polypeptidecorresponding to a biomarker is determined and compared to a controlsample.

In one embodiment, the sample is from a subject having, or suspected ofhaving, B-cell non-Hodgkin lymphoma. For example, in one embodiment thesample is a tumour sample from a subject with lymphoma. In oneembodiment, the sample is a tumour biopsy of lymphoid tissue.

In one embodiment, the method comprises testing the sample for mutationsin one or more biomarkers listed in Table 1. In one embodiment, themethod comprises testing the sample for a plurality of the biomarkerslisted in Table 1. For example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, or 15 or more of the biomarkers may be tested for mutations.

In one embodiment the method comprises testing one or more histonemodifying genes. For example, in one embodiment the method comprisestesting one or more of MLL2, MEF2B, CREBBP, EP300, EZH2 or H3K27. In oneembodiment, the method comprises testing one or more of FOX01, CCND3,BTG2 and B2M. In one embodiment, the method comprises testing one ormore of BTG1, GNA13, SGK1, MLL2 and MEF2B. In one embodiment, the methodcomprises testing one or more of EZH2, TNFRS14, CREBP, BCL10, BTG1,GNA13, SGK1, MLL2 and MEF2B.

Methods for Classifying B-Cell NHLs

In another aspect of the disclosure there is provided a method ofclassifying a subject suspected of having, or having, B-cell non-Hodgkinlymphoma (NHL) comprising testing the sample for a mutation in one ormore biomarkers selected from MEF2B, SGK1, GNA13, and TNFRS14. In oneembodiment, samples that have a mutation in MEF2B, SGK1, GNA13, orTNFRS14 are classified as having germinal centre B-cell (GCB) diffuselarge B cell lymphoma (DLBCL). Optionally, the method further comprisestesting the sample for mutations in additional genes known to be mutatedin GCB such as BCL2, TP53 or EZH2. Optionally, the method comprisestesting the sample for mutations in one or more the biomarkers listed inTable 1. Optionally, the method comprises testing the sample for one ormore of the mutations listed in Tables 3, 5, 6, 7 or 9.

In another embodiment, there is provided a method of classifying asubject having, or suspected of having, B-cell non-Hodgkin lymphoma(NHL) comprising testing a sample from the subject for a mutation inMYD88 or CD79B. In one embodiment, samples that have a mutation in MYD88or CD79B are classified as having activated B-cell (ABC) diffuse large Bcell lymphoma. Optionally, the method comprises testing the sample formutations in one or more the biomarkers listed in Table 1. Optionally,the method comprises screening the sample for one or more of themutations listed in Tables 3, 5, 6, 7 or 9.

Classifying subjects with B-cell NHL into subtypes provides a morespecific clinical diagnosis and facilitates selecting therapeutictreatment options for patients. In one embodiment, the methods describedherein can be used to select a treatment for the subject based on theclassification of a sample form the subject as GCB DLBCL or ABC DLBCL.For example, in one embodiment, subjects are classified as havinggerminal centre B-cell (GCB) diffuse large B cell lymphoma (DLBCL) andthe treatment that is selected comprises administration of a histonedeacetylase (HDAC) inhibitor-class drugs.

In another embodiment, the methods described herein can be used tomonitor a subject with B-cell NHL. For example, in one embodiment thebiomarkers described herein can be used to test a first sample from asubject and compare the results to a second sample taken from thesubject at an earlier or later time point. In one embodiment, anincrease in the number of mutations in the biomarkers described hereinover time indicates a progression or worsening of the disease in thesubject. In one embodiment, a reduction in the number of mutations inthe biomarkers described herein over time indicates an improvement orremission of the disease in the subject. Optionally, one or more of thebiomarkers listed in Table 1, or any combination thereof, can be testedin the methods for identifying, classifying or monitoring a subject asdescribed herein.

While the present disclosure has been described with reference to whatare presently considered to be the preferred examples, it is to beunderstood that the disclosure is not limited to the disclosed examples.To the contrary, the disclosure is intended to cover variousmodifications and equivalent arrangements included within the spirit andscope of the appended claims.

All publications, patents and patent applications are hereinincorporated by reference in their entirety to the same extent as ifeach individual publication, patent or patent application wasspecifically and individually indicated to be incorporated by referencein its entirety. Sequences associated with accession numbers or otheridentifiers described herein including for example the Tables andFigures, are herein specifically incorporated by reference.

The following non-limiting example is illustrative of the presentdisclosure:

Example 1 Identification of Recurrently Mutated Genes

The genomes or exomes of 14 NHL cases were sequenced, all with matchedconstitutional DNA sequenced to comparable depths. After screening forsingle nucleotide variants followed by subtraction of knownpolymorphisms and visual inspection of the sequence read alignments, 717nonsynonymous (coding single nucleotide variants; cSNVs) affecting 651genes were identified. Between 20 and 135 cSNVs in each of these genomeswere identified. Only 25 of the 651 genes with cSNVs were represented inthe cancer gene census (December, 2010 release) [14].

RNA sequencing (RNA-seq) was performed on these 14 NHL cases and anexpanded set of 113 samples comprising 83 DLBCL, 12 FL and 8 B-cell NHLcases with other histologies and 10 DLBCL-derived cell lines. These datawere analysed to identify novel fusion transcripts and cSNVs (FIG. 1).240 genes were identified with at least one cSNV in a genome/exome or anRNA-seq “mutation hot spot” (below), and with cSNVs in at least threecases in total. cSNVs were selected from each of these 240 genes forre-sequencing to confirm their somatic status. Genes with previouslydocumented mutations in lymphoma (e.g. CD79B, BCL2) were notre-sequenced. The somatic status of 543 cSNVs in 317 genes wasconfirmed, with 109 genes having at least two confirmed somaticmutations. A selection of these mutations is presented for biomarkersfor B-cell NHL in Table 3. Of the successfully re-sequenced cSNVspredicted from the genomes, 171 (94.5%) were confirmed somatic, 7 werefalse calls and 3 were present in the germ line. These 109 recurrentlymutated genes were significantly enriched for genes implicated inlymphocyte activation (P=8.3×10; e.g. STAT6, BCL10), lymphocytedifferentiation (P=3.5×10⁻³; e.g. CARD11), and regulation of apoptosis(P=1.9×10⁻³; e.g. BTG1, BTG2). Also significantly enriched were geneslinked to transcriptional regulation (P=5.4×10⁻⁴; e.g. TP53) and genesinvolved in methylation (P=2.2×10⁻⁴) and acetylation (P=1.2×10⁻²),including histone methyltransferase (HMT) and acetyltransferase (HAT)enzymes known previously to be mutated in lymphoma (e.g. EZH2 [13] andCREBBP [15]).

Mutation hot spots can result from mutations at sites under strongselective pressure and such sites have previously been identified usingRNA-seq data [13]. Therefore, RNA-seq data was searched for genes withmutation hot spots, and 10 genes were identified that were not mutatedin the 14 genomes (PIM1, FOXO1, CCND3, TP53, IRF4, BTG2, CD79B, BCL7A,IKZF3 and B2M), of which five (FOXO1, CCND3, BTG2, IKZF3 and B2M) werenot previously known targets of point mutation in NHL (Table 4). FOXO1,BCL7A and B2M exhibited hot spots affecting their start codons. Theeffect of a FOXO1 start codon mutation, which was observed in threecases, was further studied using a cell line in which the initiating ATGwas mutated to TTG. Western blots probed with a FOXO1 antibody revealeda band with a reduced molecular weight, indicative of a FOXO1 N-terminaltruncation (FIG. 4) consistent with utilization of the next in-frame ATGfor translation initiation. A second hot spot in FOXO1 at T24 wasmutated in two cases. T24 is reportedly phosphorylated by AKT subsequentto B-cell receptor (BCR) stimulation [16] inducing FOXO1 nuclear export.

The RNA-seq data was analysed to determine whether any of the somaticmutations in the 109 recurrently mutated genes showed evidence forallelic imbalance with expression favouring one allele. Of 380 expressedheterozygous mutant alleles, preferential expression of the mutation wasobserved for 16.8% (64/380) and preferential expression of the wild-typewas observed for 27.8% (106/380). Seven genes displayed evidence forsignificant preferential expression of the mutant allele in at least twocases: (BCL2, CARD11, CD79B, EZH2, IRF4, MEF2B and TP53). In 27 of 43cases with BCL2 cSNVs, expression favoured the mutant allele, consistentwith the previously-described hypothesis that the translocated (andhence, transcriptionally deregulated) allele of BCL2 is targeted bysomatic hypermutation [17]. Examples of mutations at known oncogenic hotspot sites such as F123I in CARD11 [18] exhibited allelic imbalancefavouring the mutant allele in some cases. Similarly, expressionfavouring two novel hot spot mutations in MEF2B (Y69 and D83) wasobserved and two sites in EZH2 not previously reported as mutated inlymphoma (A682G and A692V).

To distinguish new cancer-related mutations from passenger mutations,the approach proposed by Greenman et al. was used [19]. 26 genes wereidentified with significant evidence for positive selection (FDR 0.03,Methods), with either selective pressure for acquiring non-synonymouspoint mutations or truncating/nonsense mutations (Table 1). Includedwere known lymphoma oncogenes (BCL2, CD79B [9], CARD11 [18], MYD88 [10]and EZH2 [13]), all of which exhibited signatures indicative ofselection for non-synonymous variants.

Evidence for Selection of Inactivating Changes

Tumour suppressor genes were expected to exhibit strong selection forthe acquisition of nonsense mutations. The eight most significant genesincluded seven with strong selective pressure for nonsense mutations,including the known tumour suppressor genes TP53 and TNFRSF14 [20](Table 1). CREBBP, recently reported as commonly inactivated in DLBCL[15], also showed some evidence for acquisition of nonsense mutationsand cSNVs (Table 5). Enrichment was observed for nonsense mutations inBCL10, a positive regulator of NF-κB, in which oncogenic truncatedproducts have been described in lymphomas [21]. The remaining stronglysignificant genes (BTG1, GNA13, SGK1 and MLL2) had no reported role inlymphoma. GNA13 was affected by mutations in 22 cases including multiplenonsense mutations. GNA13 encodes the alpha subunit of a heterotrimericG-protein coupled receptor responsible for modulating RhoA activity[22]. Some of the mutated residues negatively impact its function [23,24], including a T203A mutation, which also exhibited allelic imbalancefavouring the mutant allele. GNA13 protein was reduced or absent onWestern blots in cell lines harbouring either a nonsense mutation, astop codon deletion, a frame shifting deletion, or changes affectingsplice sites (FIG. 5).

SGK1 encodes a PI3K-regulated kinase with functions including regulationof FOXO transcription factors [25], regulation of NF-κB byphosphorylating IkB kinase [26], and negative regulation of NOTCHsignalling [27]. SGK1 also resides within a region of chromosome 6commonly deleted in DLBCL (FIG. 1) [5]. The mechanism by which SGK1 andGNA13 inactivation may contribute to lymphoma is unclear but the strongdegree of apparent selection towards their inactivation and theiroverall high mutation frequency (each mutated in 18 of 106 DLBCL cases)suggests that their loss contributes to B-cell NHL. Certain genes areknown to be mutated more commonly in GCB DLBCLs (e.g. TP53 [28] and EZH2[13]). Here, both SGK1 and GNA13 mutations were found only in GCB cases(P=1.93×10-3 and 2.28×10-4, Fisher exact test; n=15 and 18,respectively) (FIG. 2). Two additional genes (MEF2B and TNFRSF14) withno previously described role in DLBCL showed a similar restriction toGCB cases (FIG. 2).

Inactivating MLL2 Mutations

MLL2 exhibited the most significant evidence for selection and thelargest number of nonsense SNVs was MLL2. RNA-seq analysis indicatedthat 26.0% (33/127) of cases carried at least one MLL2 cSNV. To addressthe possibility that variable RNA-seq coverage of MLL2 failed to capturesome mutations, the entire MLL2 locus (˜36 kb) was PCR amplified in 89cases (35 primary FLs, 17 DLBCL cell lines, and 37 DLBCLs). 58 of thesecases were among the RNA-seq cohort. Illumina amplicon resequencingrevealed 78 mutations, confirming the RNA-seq mutations in theoverlapping cases and identifying 33 additional mutations. The somaticstatus of 46 variants was confirmed using Sanger sequencing (Table 6),and showed that 20 of the 33 additional mutations were insertions ordeletions (indels). Three SNVs at splice sites were also detected, aswere 10 new cSNVs that had not been detected by RNA-seq.

The somatic mutations were distributed across MLL2 (FIG. 3A). 37%(n=29/78) of these were nonsense mutations, 46% (n=36/78) were indelsthat altered the reading frame, 8% (n=6/78) were point mutations atsplice sites and 9% (n=7/78) were non-synonymous amino acidsubstitutions (Table 2). Four of the somatic splice site mutations hadeffects on MLL2 transcript length and structure. For example, twoheterozygous splice site mutations resulted in the use of a novel splicedonor site and an intron retention event.

Approximately half of the NHL cases sequenced had two MLL2 mutations(Table 6). BAC clone sequencing was used in eight FL cases to show thatin all eight cases the mutations were in trans, affecting both MLL2alleles. This observation is consistent with the notion that there is acomplete, or near-complete, loss of MLL2 in the tumour cells of suchpatients.

With the exception of two primary FL cases and two DLBCL cell lines(Pfeiffer and SU-DHL-9), the majority of MLL2 mutations appeared to beheterozygous. Analysis of Affymetrix 500k SNP array data from two FLcases with apparent homozygous mutations revealed that both tumoursexhibited copy number neutral loss of heterozygosity (LOH) for theregion of chromosome 12 containing MLL2 (Methods). Thus, in addition tobi-allelic mutation, LOH is a second, albeit less common mechanism bywhich MLL2 function is lost.

MLL2 was the most frequently mutated gene in FL, and among the mostfrequently mutated genes in DLBCL (FIG. 2). MLL2 mutations wereconfirmed in 31 of 35 FL patients (89%), in 12 of 37 DLBCL patients(32%), in 10 of 17 DLBCL cell lines (59%) and in none of the eightnormal centroblast samples sequenced. The analysis predicted that themajority of the somatic mutations observed in MLL2 were inactivating(91% disrupted the reading frame or were truncating point mutations),suggesting that MLL2 is a tumour suppressor of significance in NHL.

Recurrent Point Mutations in MEF2B

Selective pressure analysis also revealed genes with stronger pressurefor acquisition of amino acid substitutions than for nonsense mutations.One such gene was MEF2B, which had not previously been linked tolymphoma. 20 (15.7%) cases had MEF2B cSNVs and 4 (3.1%) cases had MEF2CcSNVs. All cSNVs detected by RNA-seq affected either the MADS box orMEF2 domains. To determine the frequency and scope of MEF2B mutations,exons 2 and 3 were Sanger-sequences in 261 primary FL samples; 259 DLBCLprimary tumours; 17 cell lines; 35 cases of assorted NHL (IBL, compositeFL and PBMCL); and eight non-malignant centroblast samples. A capturestrategy was also used to sequence the entire MEF2B coding region in the261 FL samples, revealing six additional variants outside exons 2 and 3.69 cases (34 DLBCL; 12.67% and 35 FL; 15.33%) were identified with MEF2BcSNVs or indels; novel variants in other NHL and non-malignant sampleswere not observed. 55 (80%) of the variants affected residues within theMADS box and MEF2 domains encoded by exons 2 and 3 (Table 7; FIG. 3B).Each patient generally had a single MEF2B variant and relatively few (8total, 10.7%) truncation-inducing SNVs or indels were observed.Non-synonymous SNVs were by far the most common type of change observed,with 59.4% of detected variants affecting K4, Y69, N81 or D83. In 12cases MEF2B mutations were shown to be somatic, including representativemutations at each of K4, Y69, N81 and D83 (Table 8). Mutations in ABCcases were not detected, indicating that somatic mutations in MEF2B playa role unique to the development of GCB DLBCL and FL (FIG. 2).

Discussion

In this study of genome, transcriptome and exome sequences from 127B-cell NHL cases, 109 genes were identified with clear evidence ofsomatic mutation in multiple individuals. Significant selection appearsto act on at least 26 of these for the acquisition of either nonsense ormissense mutations. The majority of these genes do not appear to havepreviously been associated with any cancer type. An enrichment ofsomatic mutations was observed affecting genes involved intranscriptional regulation and, more specifically, chromatinmodification.

MLL2 emerged from the analysis as a major tumour suppressor locus inNHL. It is one of six human H3K4-specific methyltransferases in the MLLfamily, all of which share homology with the Drosophila trithorax gene[29]. Trimethylated H3K4 (H3K4me3) is an epigenetic mark associated withthe promoters of actively transcribed genes. By laying down this mark,MLLs are responsible for the transcriptional regulation of developmentalgenes including the homeobox (Hox) gene family [30] which collectivelycontrol segment specificity and cell fate in the developing embryo[31,32]. Each MLL family member is thought to target different subsetsof Hox genes [33] and in addition, MLL2 is known to regulate thetranscription of a diverse set of genes [34]. Recently, MLL2 mutationswere reported in a small-cell lung cancer cell line [35] and in renalcarcinoma [36] but the frequency of nonsense mutations affecting MLL2 inthese cancers was not established in these reports. Parsons andcolleagues recently reported inactivating mutations in MLL2 or MLL3 in16% of medulloblastoma patients [37] further implicating MLL2 as acancer gene.

The data in this example link MLL2 somatic mutations to B-cell NHL. Thereported mutations are likely to be inactivating and in eight of thecases with multiple mutations, it was confirmed that both alleles wereaffected, presumably resulting in essentially complete loss of MLL2function. The high prevalence of MLL2 mutations in FL (89%) equals thefrequency of the t(14;18)(q32;q21) translocation, which is consideredthe most prevalent genetic abnormality in FL [3]. In DLBCL tumoursamples and cell lines, MLL2 mutation frequencies were 32% and 59%respectively, also exceeding the prevalence of the most frequentcytogenetic abnormalities, such as the various translocations involving3q27, which occur in 25-30% of DLBCLs and are enriched in ABC cases[38]. Importantly, MLL2 was found mutated in both DLBCL subtypes (FIG.2). Analyses thus indicate that MLL2 acts as a central tumour suppressorin FL and both DLBCL subtypes.

The MEF2 gene family encodes four related transcription factors thatrecruit histone-modifying enzymes including histone deacetylases (HDACs)and HATs in a calcium-regulated manner. Although truncating variantswere detected in MEF2 gene family members, the present analysis suggeststhat, in contrast to MLL2, MEF2 family members tend to selectivelyacquire non-synonymous amino acid substitutions. In the case of MEF2B,59.4% of all the cSNVs were found at four sites within the protein (K4,Y69, N81 and D83), and all four of these sites were confirmed to betargets of somatic mutation. 39% of the MEF2B alterations affect D83,resulting in replacement of the charged aspartate with any of alanine,glycine or valine. Although the specific the consequences of thesesubstitutions on protein function is unknown, it seems likely that theireffect would impact the ability of MEF2B to facilitate gene expressionand thus play a role in promoting the malignant transformation ofgerminal centre B cells to lymphoma.

MEF2B mutations can be linked to CREBBP and EP300 mutations, and torecurrent Y641 mutations in EZH2 [13]. One target of CREBBP/EP300 HATactivity is H3K27, which is methylated by EZH2 to repress transcription.There is evidence that the action of EZH2 antagonizes that ofCREBBP/EP300 [39]. One function of MEF2 is to recruit either HDACs orCREBBP/EP300 to target genes [40], and it has been suggested that HDACscompete with CREBBP/EP300 for the same binding site on MEF2 [41]. Undernormal Ca²⁺ levels, MEF2 is bound by type IIa HDACs, which maintain thetails of histone proteins in a deacetylated repressive chromatin state[42]. Increased cytoplasmic Ca²⁺ levels induce the nuclear export ofHDACs, enabling the recruitment of HATs such as CREBBP/EP300,facilitating transcription at MEF2 target genes. Mutation of CREBBP,EP300 or MEF2B may impact expression of MEF2 target genes owing toreduced acetylation of nucleosomes near these genes (FIG. 6). In lightof the recent finding that heterozygous EZH2 Y641 mutations enhanceoverall H3K27 trimethylation activity of PCR2 [43, 44], it is possiblethat mutation of both MLL2 and EZH2 could cooperate in reducing theexpression of some of the same target genes. The data in this exampleshow that (1) post-transcriptional modification of histones is of keyimportance in germinal centre B cells and (2) deregulated histonemodification due to these mutations likely results in reducedacetylation and enhanced methylation and acts as a core driver event inthe development of NHL (FIG. 6).

It is thought that GCB and ABC DLBCLs arise due to distinct geneticevents [5] and it is widely accepted that the aggressive nature of thelatter results from the acquisition of mutations that mimic stimulationof the B cell receptor by antigen or those that more directly induceconstitutive activation of NF-κB [2]. This example provides otherimportant modulators or components of BCR signalling and regulators of Bcell differentiation or survival as targets of repeated and recurrentmutation, including MEF2B/C [79], SGK [5], IRF4 [82], STAT3 [77], STAT6[83], RFTN1 [84], CCND3 [85], PLCG2, FOXO1 [86], CARD11 [18], CD79B [9]and MYD88 [10] and IKZF3 [87]. There were notable differences inmutation patterns among these genes. For example, MEF2B/C and STAT3,each of which function as dimers, showed strong evidence for selectivelyacquiring nonsynonymous (rather than truncating) mutations, whereas SGK1and CCND3 appeared to be preferentially truncated in NHL. The previouslycharacterized CARD11 [18], CD79B [9] and MYD88 [10] all act upstream ofNF-κB, leading to its deregulation, typically in ABC DLBCLs. In thepresent Example, only CD79B and MYD88 (in addition to structuralrearrangements involving BCL6) showed a significant enrichment formutations in ABC cases (FIG. 2) and the point mutations observed largelycorresponded to the known hot spots in these two genes [9, 10] (Table4).

The remaining genes listed above encode proteins that are eitheractivated or inhibited as a result of BCR stimulation, but not directlyinvolved in regulating NF-κB. PRDM1 has been termed the plasma cellmaster differentiation gene as it orchestrates terminal differentiationof germinal centre B cells into plasma cells [88]. Importantly STAT3[77], found here to be commonly mutated in DLBCL, regulates the activityor expression of PRDM1 in response to IL-21 stimulation. Of interest,inherited mutations in STAT3 are the primary cause of an immune disorderknown as hyper IgE syndrome and it has been shown that in these casesmutant STAT3 acts in a dominant negative manner [89]. Strikingly, someof the somatic mutations reported here affect the same residues foundmutated in the constitutional DNA of hyper IgE patients. This leads to aprediction that mutant cells may be unable to induce PRDM1 transcriptionfollowing IL-21 stimulation (FIG. 6A). In particular, as many of thesemutations were found in both GCB DLBCL and FL, the data suggests thatmalignant transformation of germinal centre B cells relies on componentsof BCR signalling separate from those utilized in ABC DLBCL (i.e. NF-κB)but also that altered regulation of PRDM1, previously thought to be afeature unique to ABC DLBCL, may be of general importance in NHL.

Mutations affecting CREBBP and EP300 were recently reported in DLBCL[15], and ALL [90]. Similar to the observations reported in thesestudies, the data shows a preference for accumulation of truncating SNVs(n=4, 16.7% of mutated cases) but also include non-synonymous SNVs inmany cases (20 cases with cSNVs, Table 5). EP300 also contained multiplecSNVs (8 cases total). 3 EP300 cSNVs and 9 CREBBP cSNVs were confirmedas somatic mutations. Cases with multiple cSNVs in either gene wererarely observed (one cell line and three patients) consistent with thecommonly held notion that both genes are haploinsufficient [91]. ThecSNVs that were not predicted to result in protein truncation weremainly found within the HAT domain of these two proteins. These includedfour codons that are apparent mutation hot spots (Tables 4 and 5). Ofthese, three correspond to residues that have been reported to behomologous between the two proteins [75] (Table 5). Representative cSNVscorresponding to three of these hot spots in CREBBP and one in EP300were confirmed as somatic. Three of the EP300 somatic non-synonymousmutations observed affected residues previously shown to reduceacetyltransferase activity in an in vitro acetyltransferase assay[75].CREBBP (but not EP300) was confirmed to have a significant signature ofselective pressure to acquire both truncating and missense mutations(Table 1), but the lack of significance for the latter may owe tolimited statistical power due to its reduced mutation prevalencerelative to CREBBP. Taken together, these data suggest that reduction orloss of either CREBBP or EP300 may promote lymphomagenesis. Of note, incontrast to a recent report [15], a significant difference was notobserved in CREBBP or EP300 mutation frequency in the two subtypes(P=0.5656 for CREBBP and 0.6607 for EP300; Fisher exact test).

MEF2 proteins can act as transcriptional co-activators or co-repressorsby recruiting two classes of enzymes that alter the acetylation state ofhistone tails, namely HATs and HDACs. MEF2 dimers are known to associatewith the two HATs CREBBP and EP300 [30] and it has been suggested thatHDACs and CREBBP/EP300 compete for the same binding site on MEF2 [41].Under normal levels of intracellular Ca²⁺, MEF2 is bound by one ofseveral type IIa HDACs, which maintain the tails of histone proteins ina deacetylated repressive chromatin state [42]. Increased cytoplasmicCa²⁺ levels induce the nuclear export of the bound HDAC, thus enablingMEF2 dimers to recruit a HAT enzyme such as CREBBP/EP300, whichfacilitate transcription at MEF2 target genes by catalysing the additionof acetyl groups to the tails of core histone proteins including lysine27 on histone H3 (H3K27) [40, 41] (FIG. 6D).

Ca²⁺-mediated induction of MEF2 target genes is utilised in diversedevelopmental processes including muscle and neuronal celldifferentiation [92] as well as the maturation of B and T cells [80].For example, during negative selection, upon T-cell-receptor (TCR)stimulation, the resulting Ca²⁺ influx results in MEF2-mediatedinduction of the pro-apoptosis NR4A1 (NUR77), which, in turn drivesapoptosis of self-reactive T cells [80]. It has also been shown in Tcells that MEF2D interacts directly with nuclear NFAT, anotherCa²⁺/CaM-regulated protein, and recruits EP300 to MEF2 target genes[93]. In murine B cells, it was recently demonstrated that MEF2C isrequired to mediate gene expression events following BCR stimulation,but this study did not discuss a possible overlapping role of MEF2B inthis process nor was there a conclusive identification of theMEF2C-regulated genes important to this process [79]. That mutations inMEF2C were also observed at a lower frequency in NHL samples supportsthe interpretation that these proteins share a related function in thiscellular context. The MEF2B dimer has previously been co-crystallizedwith three of its interacting partners, namely Cabin1 [81], HDAC9 [41]and EP300 [50] and, informed by these structures, one could predict thatmany of the recurrent mutations would negatively impact the function ofMEF2B. For example, at least three of the mutated residues (K5, K23 andR24) are required for mediating the binding of MEF2 to DNA [94]. BecauseMEF2 proteins can heterodimerize [95], mutations that impact thefunction of MEF2 are known to produce a dominant effect on the overallfunction of any MEF2-family protein by occupying a significantproportion of MEF2-containing complexes [96]. In fact one of theresidues found mutated in this study (K24) was previously demonstratedto act as a dominant negative when ectopically expressed [96]. Further,the mutation hot spot Y69 was recently shown to be involved in multipleinteractions in a solved crystal structure of MEF2B bound to EP300 [50],suggesting the possibility that this mutation may impact the ability ofthese two proteins to interact. Although the impact of the individualMEF2B mutations on MEF2 function requires further study, the recurrenceof these mutations among a limited set of residues suggests the actionof positive selection for these mutations during cancer progression.

When one considers the high frequency of mutations detected that affectgenes encoding MEF2 proteins, it is striking that inactivating mutationsaffecting both CREBBP and EP300 are common in NHL, as these are bothknown effectors of the induction of MEF2-regulated genes. Notably, withone exception, all of the truncation-inducing mutations identified inCREBBP and EP300 are predicted to remove the histone acetyltransferase(HAT) domain of the protein [81]. Moreover, comparison of the positionsmutated in CREBBP to those mutated in EP300 reveals that some homologousresidues within the HAT domains are affected in both proteins. Based onthe crystal structure of EP300, five of these recurrently mutatedresidues were previously identified as important for mediating substrateinteraction [75]. In that study, three of these residues were mutatedand showed loss (or reduction) of HAT activity in vitro, suggesting thatmany of the cSNVs observed in these two proteins also negatively impacttheir function in vivo. Further, CREBBP/EP300 are both known to regulatethe function of FOXO1 [97], another gene found recurrently mutated inthis study. Thus it is also possible that the mutation of these genes inaddition their potential effect on MEF2-mediated transactivation, couldimpact the normal AKT-mediated nuclear exclusion of FOXO1 (FIG. 6C).

The data presented herein is consistent with a model wherein theinduction of MEF2 target genes in response to BCR stimulation isinhibited by mutations that reduce the function of MEF2 complexes,potentially in a dominant negative fashion, or mutations that inactivateeither of their transcriptional co-activators CREBBP or EP300 (FIG. 6D).Another mutation identified herein in a single case is also consistentwith this model, namely the mutation of S155 to phenylalanine in HDAC7.This serine residue is known to be phosphorylated by CAMK following TCRstimulation, facilitating nuclear export of HDAC7 in response to Ca²⁺influx [98]. In the cited study, mutation of this residue resulted inimpaired export of HDAC7 following TCR stimulation thereby inhibitingMEF2-mediated induction of NUR77 expression and hence, inhibitingNUR77-mediated apoptosis. Thus, this mutant could potentially produce anuclear-restricted protein that leads to constitutive suppression ofMEF2 target genes regardless of intracellular Ca²⁺ levels. This would bea similar effect that would be expected for loss-of-function mutationsof MEF2B, CREBBP or EP300. Though an increase in cytoplasmic Ca²⁺ is onedownstream signal following BCR stimulation, the NFAT transcriptionfactors, key downstream mediators of this signal that promote survival,were not mutated and thus are expected to function normally. Also,pathways such as NF-κB and events modulated by AKT do not rely on theCa²⁺ messenger and should therefore be unaffected by these mutations.Interestingly, a recent report suggests that SGK1 (found here to becommonly inactivated in DLBCL) may also play a role in modulating Ca²⁺levels by regulating the turnover of the Ca²⁺ channel protein Orai [99].Thus, this model predicts that mutations directly affecting MEF2function (i.e. those in MEF2B, MEF2C, HDAC7, CREBBP or EP300) or othergenes involved in regulating cytoplasmic calcium levels would diminishthe cell's ability to induce MEF2 target genes in response to BCRstimulation while leaving other downstream signals intact.

Methods Sample Acquisition

Lymphoma samples were classified by an expert haematopathologist (R.D.G)according to the World Health Organization criteria of 2008. Benignspecimens included reactive pediatric tonsils or purified CD77-positivecentroblasts sorted from reactive tonsils using Miltenyi magnetic beads(Miltenyi Biotec, CA). The tumour specimens were collected as part of aresearch project approved by the University of British Columbia-BritishColumbia Cancer Agency Research Ethics Board (BCCA REB) and are inaccordance with the Declaration of Helsinki.

For all DLBCL samples profiled by RNA-seq, genome or exome sequencing inthis study, tumour content was greater than 50% as assessed by: a)immunophenotyping using flow cytometry to detect the level ofcoexpression of CD19 and light chain restriction; or b) a pathologistreview of an H&E-stained frozen section taken adjacent to the tissuethat was cut and used for nucleic acid extraction. All other specimensused in this study were obtained at the time of diagnosis and werederived from archived fresh-frozen tissue or frozen tumour cellsuspensions. Constitutional DNA was obtained from peripheral blood orfrom B cell-negative sorted tumour cell suspensions (fraction elutedfrom cells captured by B Cell Isolation Kit II or CD19 MicroBeads(Miltenyi Biotec, CA)).

Cell Lines

DB [51], DOHH-2 [52], Karpas422 [53], NU-DHL-1 [54], NU-DUL-1 [55],SU-DHL-6 and WSU-DLCL2 [56] are cell lines obtained from DSMZ. Pfeifferand Toledo were obtained from ATCC and all OCI-Ly [57] lines (1, 3, 7,10 and 19) were obtained from Louis Staudt (US National Institutes ofHealth). The cell lines MD903, SU-DHL-9 and RIVA were obtained fromMartin Dyer (University of Leicester, UK).

Preparation and Sequencing of RNA-Seq, Genome and Exon Capture IlluminaLibraries

Genomic DNA for construction of genome and exome libraries was preparedfrom biopsy materials using the Qiagen AllPrep DNA/RNA Mini Kit(Qiagen). DNA quality was assessed by spectrophotometry (260 nm/280 nmand 260 nm/230 nm absorption ratios) and gel electrophoresis beforelibrary construction. DNA was sheared for 10 minutes using a SonicDismembrator 550 with a power setting of “7” in pulses of 30 secondsinterspersed with 30 seconds of cooling (Cup Horn, Fisher Scientific)and then analysed on 8% PAGE gels. The 200 to 300 bp DNA size fractionwas excised and eluted from the gel slice overnight at 4° C. in 300 μLof elution buffer (5:1 (vol/vol) LoTE buffer (3 mM Tris-HCl, pH 7.5, 0.2mM EDTA)/7.5 M ammonium acetate) and was purified using a Spin-X FilterTube (Fisher Scientific) and ethanol precipitation. Genome librarieswere prepared using a modified paired-end protocol supplied by IlluminaInc. This involved DNA end-repair and formation of 3′ adenosineoverhangs using the Klenow fragment of DNA polymerase I (3′-5′exonuclease minus) and ligation to Illumina PE adapters (with 5′overhangs). Adapter-ligated products were purified on QIAquick spincolumns (Qiagen) and PCR-amplified using Phusion DNA polymerase (NEB)and ten cycles with the PE primer 1.0 and 2.0 (Illumina). PCR productsof the desired size range were purified from adapter ligation artifactsusing 8% PAGE gels. DNA quality was assessed and quantified using anAgilent DNA 1000 series II assay (Agilent) and Nanodrop 7500spectrophotometer (Nanodrop), and DNA was subsequently diluted to 10 nM.The final concentration was confirmed using a Quant-iT dsDNA HS assaykit and Qubit fluorometer (Invitrogen).

For genomic DNA sequencing, clusters were generated on the Illuminacluster stations using v1 cluster reagents. Paired-end reads weregenerated using v3 sequencing reagents on the Illumina GA_(iix) platformfollowing the manufacturer's instructions. Image analysis, base-callingand error calibration were performed using v1.0 of Illumina's Genomeanalysis pipeline. The DLBCL genomes were sequenced with 100 nucleotidepaired-end reads using the HiSeq2000 platform. For RNA-seq analysis, amodified method was used similar to the protocol previously described[13]. Briefly, RNA was extracted from 15×20 μm sections cut fromfresh-frozen lymph node biopsies using the MACS mRNA isolation kit(Miltenyi Biotec), from 5-10 μg of DNase I-treated total RNA as per themanufacturer's instructions. Double-stranded cDNA was synthesized fromthe purified poly(A)⁺ RNA using the Superscript Double-Stranded cDNASynthesis kit (Invitrogen) and random hexamer primers (Invitrogen) at aconcentration of 5 μM. The cDNA was fragmented by sonication and apaired-end sequencing library prepared following the Illumina paired-endlibrary preparation protocol (Illumina).

For exome sequencing, genomic DNA was extracted following the protocolsupplied in the Qiagen AllPrep DNA/RNA Mini Kit (Cat#80204), andquantified using a Quant-iT dsDNA HS assay kit and a Qubit fluorometer(Invitrogen). Approximately 500 ng DNA was sheared for 75 seconds atduty cycle “20%” and intensity of “5” using a Covaris E210, and run onan 8% PAGE gel. A 200 to 250 bp DNA size fraction was excised and elutedfrom the gel slice, and was ligated to Illumina paired-end adaptersfollowing a standard protocol as previously described [13]. The adapterligated DNA was amplified for 10 cycles using the PE primer set(Illumina) and purified as a pre-exome capture library. The DNA wasassessed using an Agilent DNA 1000 Series II assay, and 500 ng DNA washybridized to the 38 Mb Human exon probe using the All Exon Kit(Cat#G3362) following the Agilent SureSelect Paired-End TargetEnrichment System Protocol (Version 1.0, September 2009). The capturedDNA was purified using a Qiagen MinElute column, and amplified for 12cycles using PE primer set. The PCR products were run on an 8% PAGE gel,the desired size range (320 to 370 bp) was excised and purified, and wasthen assessed using an Agilent DNA 1000 series II assay and diluted to10 nM. The final library DNA concentration was confirmed using aQuant-iT dsDNA HS assay kit and Qubit fluorometer. Clusters weregenerated on the Illumina cluster station and paired-end reads generatedusing an Illumina Genome Analyzer (GA_(IIx)) following themanufacturer's instructions.

Alignment-Based Analysis of Tumour DNA and RNA Sequence for SomaticPoint Mutations

All reads were aligned to the human reference genome (hg18) or (forRNA-seq) to a genome file that was augmented with a set of all exon-exonjunction sequences using BWA version 0.5.4 [46]. RNA-seq libraries werealigned with an in-house modified version of BWA that is aware of exonjunction reads and considers them when determining pairing distance inthe “sampe” (read pairing) phase of alignment. Candidatesingle-nucleotide variants (SNVs) were identified in the aligned genomicsequence reads and the transcriptome (RNA-seq) reads using an approachsimilar to one we previously described [13]. One key difference in thevariant calling in this study was the application of a Bayesian SNVidentification algorithm (‘SNVmix’) [47]. This approach is able toidentify SNVs with a minimum coverage of two high-quality (Q20) bases.SNVs were retained if they had a SNVmix probability of at least 0.99 andhad support from reads mapping to both genomic strands. Any SNV neargapped alignments or exactly overlapping sites assessed as beingpolymorphisms (SNPs) were disregarded, including variants matching aposition in dbSNP or the sequenced personal genomes of Venter [58],Watson [59] or the anonymous Asian [60] and Yoruban [61] individuals.For paired samples with matched constitutional DNA sequence, allvariants with evidence (a SNVmix probability of at least 0.99 and 2 ormore high quality base calls matching the SNV) in the constitutional DNAwere considered germline variants and were no longer considered cSNVs.Mutations were annotated on genes using the Ensembl transcripts (version54), except in the cases of MEF2B and MLL2, for which the Ensemblannotations were deemed inferior to the Refseq. Because situations wereobserved where exons were represented in Ensembl transcripts that werenot also represented in a Refseq, candidate mutations are only reportedin exons shared by both annotations (e.g. in Supplementary Table S4).Candidate mutations were subsequently reviewed visually in theintegrative genomics viewer (IGV) [62] and those appearing to beartefacts or with some evidence (2 or more reads) visible in theconstitutional DNA sequence were removed.

Validation of Candidate Somatic Mutations Using Illumina Sequencing

Validation was accomplished by designing primers to amplify a 200 to 300bp region around the targeted variant with one primer within reach of asingle read (i.e. maintaining the sum of the primer length and distanceto variant less than 100 bp, depending on read length used). Ampliconswere generated for both tumour and normal DNA. Two pools of ampliconswere generated, one for tumour and one for normal DNA, with equalvolumes from each PCR reaction (or increased volume for amplicons thatresulted in faint bands in an agarose gel) and an Illumina paired-endsequencing library was constructed from the pool. For variants common tomore than one patient, a 6 nt index, which was added to the 5′ end ofeach primer, was assigned for each patient. These index sequences weretrimmed from sequence reads prior to alignment and subsequently used toassociate the data with individual patients. Reads were aligned usingBWA and variants were visually confirmed for validity and somatic statusin IGV [63] (absence from constitutional DNA). Variants with primerdesign or PCR failures were scored as ‘unvalidated’.

Validation of cSNVs by Sanger Sequencing

The majority of candidate cSNVs were validated by Sanger sequencing ofthe region surrounding each mutation. These included all cSNVsidentified in the two DLBCL exomes and the FL genome/exome (i.e.DLBCL-PatientA, DLBCL-PatientB and FL-PatientA). For the additionalDLBCL genomes, cSNVs were selected for validation only if there werethree or more cSNVs in that gene in the entire cohort. To do so, primerswere designed to amplify 350-1200 bp regions by PCR (most amplicons were˜400 bp). Forward and reverse primers were tailed with T7 and M13Reverse5′ priming sites, respectively. PCR conditions used were 94° C. for 2minutes, 30 cycles of 94° C. for 30 seconds, 60° C. for 30 seconds and72° C. for 1 minute, and a final extension at 72° C. for 8 minutes. Todetermine the somatic or germ line origin of the mutations, mutationswere re-sequenced in both tumour and constitutional DNA, the latterobtained from peripheral blood or negative-sort cells (see sectionentitled Sample Acquisition). The sequencing reactions consisted of 50cycles of 96° C. for 10 seconds, 43° C. (for M13Reverse) or 48° C. (T7)for 5 seconds and 60° C. for 4 minutes and were analysed using an AB3730XL. All capillary traces were analysed using the Staden Package [64]and all somatic variants were visually inspected to confirm theirpresence in tumour and absence from germ line traces. Some regions thatfailed to amplify in the first attempt were re-addressed with theaddition of 5% DMSO and 5% betaine to the sequencing reactions, butotherwise maintaining the PCR conditions. SNVs in certain genes, such asBCL7A and HDAC7, repeatedly failed to amplify and for these, it was notpossible to address whether the mutations in these genes weresomatically acquired or were present in the germ line. Validation wasnot performed for variants in BCL2 or CD79B as their somatic mutationstatus in DLBCL is well established.

Detection of Enrichment of Functional Gene Classes within FrequentlyMutated Genes

Significant functional classes represented in the cSNV list wereidentified using the DAVID Functional Annotation tool(http://david.abcc.ncifcrf.gov/). Reported P values were corrected formultiple testing using the Benjamini method.

Detection of Mutations with Imbalanced/Skewed Expression

The analysis of imbalanced expression was restricted to (1) confirmedsomatic nonsynonymous point mutations along with (2) previouslypublished hot spot mutations. In total, there were 381 such mutations in99 of the 109 genes represented in the RNA-seq data. For each mutatedgene, the number of aligned reads supporting the reference and mutantallele was determined. For genes with multiple mutations in the samepatient (e.g. BCL2), the sum of all reads supporting each of thenon-reference alleles in that patient was used instead (assuming thatall mutations were restricted to the same allele). Significantimbalance/skew was computed using the binomial exact test and P valueswere corrected using the Bonferroni method.

Calculation of Selective Pressure

To determine if mutational patterns were indicative of selectivepressure, both synonymous and non-synonymous cSNVs were consideredacross the patient cohort (excluding those found to be present in thegerm line or false positives after validation). Selection can beinferred when the type of mutations in a gene differs from thoseexpected by chance given a specific mutation profile. To analyse thesignificance of this deviation, methods described by Greenman andcolleagues [20] were applied to identify genes with signatures ofselection. This analysis was performed on the 101 (of 109 total) genesthat had, in addition to 2 or more confirmed somatic mutations, morethan 2 cSNVs in total. The coding sequence of each gene (using thelongest Refseq annotation for that gene) was scanned for all possiblesilent and non-silent mutations (missense and truncating) matching sixtypes of sequence changes (C>A, C>G, C>T, T>A, T>C, T>G). The separationof mutations into different strata allows the model to consider theoverall effect that cancer specific mutation mechanisms may have on themutation profile. A null-selection mutation profile is estimated via thesynonymous mutations, under the assumption that they do not confer anadvantage to the tumour. A score statistic describing the selectivepressure was then calculated by comparing the expected mutations of eachtype to the observed ones. Statistical significance was then determinedby constructing an empirical distribution of scores from 100,000 MonteCarlo simulations under the null hypothesis of no selection. The numberof Monte Carlo iterations was increased to a maximum of 14,600,000 forgenes that did not obtain a p-value at the default 100,000 simulations.The type and strength of the selective pressure the genes were underwere also estimated using the models described by Greenman et al. [20].This is represented by a quantitative value of less than, equal to, orlarger than 1 for negative, null, or positive selection respectively(Table 1, other data not shown).

Several genes in the list have previously been identified as targets ofsomatic hypermutation (SHM), which is mediated by the enzyme AICDA (alsoknown as AID) and targets a limited number of genes in DLBCL [65, 66].In an attempt to avoid biasing the selective pressure model with thedistinct mutational signature caused by somatic hypermutation, the geneswere split into two sets. The hypermutation set contained genespreviously reported to be targets of SHM (BCL2 [17], BCL6, IRF4, PIM1,and CIITA) and the non-hypermutation set contained the remaining 95genes. The effect of the different mutational profiles of both sets canbe appreciated by considering the BCL2 case. When inserted into themodel with the rest of the genes BCL2 presented the highest selectivepressure of all genes (65.65); however, when the selective pressuremodel was applied to the hypermutated genes separately, BCL2 selectivepressure was estimated at 3.78.

Identifying Genes with Mutation Hot Spots

Hot spots were identified by searching for clustered mutations in thecSNVs identified by RNA-seq. Owing to the lack of constitutional DNAsequence from some patient samples, whether the variants detected onlyby RNA-seq were present in the germ line could not necessarily bediscerned. Cases were sought in which codons were recurrently mutated.To find hot spots in the RNA-seq data, a search was performed for setsof distinct variants producing non-synonymous changes affecting the samecodon in different tumours. The genes that met this criterion (Table 4)included known targets of recurrent mutation (EZH2, CARD11 [18] andCD79B [9]) and three hot spots in MEF2B. Also among these genes wereknown targets of aberrant somatic hypermutation in DLBCL, includingBCL2, IRF4 [65], PIM1 [66], BCL6 [67], and BCL7A [65].

Analysis of Aligned Genomic DNA Sequence for Copy Number Alterations andLOH

For the identification of copy number variations (CNVs), sequencequality filtering was used to remove all reads of low mapping quality(Q≦10). Due to the varying numbers of sequence reads from each sample,aligned reference reads were first used to define genomic bins of equalreference coverage to which depths of alignments of sequence from eachof the tumour samples were compared. This resulted in a measurement ofthe relative number of aligned reads from the tumours and reference inbins of variable length along the genome, where bin width is inverselyproportional to the number of mapped reference reads. After an estimateof differential GC bias was used to reduce noise, an HMM was used toclassify and segment continuous regions of copy number loss, neutrality,or gain using methodology outlined previously [68].

Loss of heterozygosity was determined for each sample using the lists ofgenomic SNPs that were identified through the BWA/SNVMix pipeline. Thisanalysis allows for classification of each SNP as either heterozygous orhomozygous based on the reported SNP probabilities. For each sample,genomic bins of consistent SNP coverage were used by an HMM to identifygenomic regions of consistent rates of heterozygosity. The HMMpartitioned each tumour genome into three states: normal heterozygosity,increased homozygosity (low), and total homozygosity (high). It can beinferred that a region of low homozygosity either represents a statewhere only a portion of the cellular population had lost a copy of achromosomal region or the signal was convoluted due to contaminatingnormal cells in the tumour. Both states of reduced homozygosity aredisplayed in blue in FIG. 1, generated by Circos [69].

Assembly-Based Analysis of Tumour DNA and RNA Sequence

Reads from the individual RNA-seq libraries were assembled using ABySSas previously described [70] using multiple values of k. Iterativepairwise alignments of the contigs from the individual kmer assembliesresulted in a merged contig set that was aligned against the referenceHuman genome (hg18) using BLAT as described [48]. Putative fusions wereidentified from contigs that had alignments to two distinct genomiclocations. The putative events were filtered using evidence fromalignment of reads to contigs using Bowtie and alignments of reads tothe genome using BWA. Those events with at least four read pairs fromthe reads-to-genome alignment and two supporting reads from thereads-to-contig alignment (i.e. across the fusion breakpoint) weremanually curated to produce a final list of putative fusions. Thegenomic breakpoints for the transcriptome predicted events wereidentified manually from the alignments of the reads to the genome usingIGV. The genomic breakpoints were later confirmed by assembly usingABySS.

Putative indels were identified from alignment of the contigs to hg18using BLAT when contiguous unmatched base(s) were found in either thecontig (insertion) or reference (deletion) sequences. The events werefiltered for read support with events requiring three or more reads tobe considered in the filtered set. The filtered set was then screenedagainst dbSNP130 to find putative novel events. The resulting set wasmanually inspected using read alignments (against both the genome andcontigs) to visually confirm candidates. This approach revealed thedeletion in GNA13 shown in FIG. 5.

The splicing alterations in MLL2 (FIGS. 3B and C) and GNA13 (FIG. 5)were identified from pairwise alignments of the contigs to hg18 usingBLAT. The contig alignments were then matched against the four knowngene models to identify novel splice junctions. The putative novelsplice junctions were filtered where two or more reads were requiredacross the novel junction for the event to be considered. Manualinspection using read alignments (against both the genome and contigs)was performed to visually confirm candidates.

Cell of Origin Subtype Assignment Using RNA-Seq Expression Values

Global gene expression signatures measured with microarrays are thestandard method for classifying DLBCL samples into the two molecularsubtypes (GCB and ABC). The Bayesian method described by Wright et al.[50] was adapted to allow classification to be accomplished with theexpression values obtained from RNA-seq data. To accomplish this,expression values for each Ensembl gene model (version 54) were computedas FPKM (fragments per kilobase gene model per million, rather than RPKMto account for the use of paired-end reads) and log-transformed. Thecurrent standard approach for routinely classifying samples usingAffymetrix U133 arrays employs 186 probesets (George Wright, personalcommunication). The 165 Ensembl genes that correspond to these probesetswere used for classification by RNA-seq. The classifier was trainedusing the 43 cases previously classified as GCB and 21 classified as ABCusing Affymetrix data. The FPKM values for these genes were comparedbetween the samples with known subtypes using the T test and thoseproducing a P value<0.01 were used for the classifier. The robustness ofthis approach was tested using leave-one-out cross-validation, whichresulted in no mis-classifications. Similarly, no samples weremis-classified when all cases with known COO (based on Affymetrix data)were used to produce the classifier however there were some cases thatwere defined as unclassifiable (U) by one method and given a subtypeassignment by the other method. In such cases, the subtype assignment(rather than U) was used.

Targeted MEF2B Resequencing Using Biotinylated RNA Capture Probes

The following strategy was used to sequence the entire MEF2B locus inmultiple patient samples in multiplex. Four exonic regions of the MEF2Bgene were amplified from a template consisting of a pool of DNAs fromthree bacterial artificial chromosomes (BACs) containing the MEF2B locus(M. Nefedov, P. J. de Jong and U Surtiby, unpublished) using PCR. PCRreactions consisting of 0.5 Units Phusion DNA Polymerase (New EnglandBiolabs, Pickering, Ont.), 0.25 mM dNTPs, 3% DMSO, 0.4 μM of the forwardand reverse primer and 5 pmol template were cycled on a MJR PelletierThermocycler (model PTC-225) for 30 seconds at 98° C.; 25×{10 seconds at98° C., 30 seconds at 65° C., 30 seconds at 72° C.}; 5 minutes at 72° C.The resulting PCR amplicons, ranging in size from 342 to 474 bp, weresize selected on an 8% Novex-TBE gel (Invitrogen Canada Inc.,Burlington, Ont.), excised and eluted into 300 μL of elution buffercontaining 5:1 (vol/vol) LoTe (3 mM Tris-HCl, pH7.5, 0.2 nM EDTA)/7.5 Mammonium acetate. The eluates were purified from gel slurries bycentrifugation through Spin-X centrifuge tube filters (Fisher ScientificLtd., Nepean, Ont.), and EtOH precipitated. Purified amplicon DNAs werequantified using an Agilent DNA 1000 Series II assay (AgilentTechnologies Canada Inc., Mississauga, Ont.). Individual amplicons werepooled (equimolar) and sheared using the Covaris S2 focusedultra-sonicator (Covaris Inc., Woburn, Mass.) with the followingsettings; 10% Duty cycle, 5% Intensity, and 200 Cycles per burst for 180seconds. The resulting products were size fractioned on an 8% Novex TBEgel (Invitrogen Canada Inc.) and the 75 to 125 bp fraction isolated,purified and quantified as above. 30 ng of resulting DNA wasend-repaired, 3-prime modified with Adenosine overhangs, and ligated tocustom adapters containing T7 and T3 promoter sequences as described[71]. Adapter-ligated products were enriched by PCR as above using T3and T7 sense strand-specific primers and the following cyclingconditions; 1 min. at 98° C.; 8× {10 seconds at 98° C., 30 seconds at60° C., 30 seconds at 72° C.}; 5 minutes at 72° C. The amplifiedproducts were separated from excess adapter on an 8% Novex TBE gel(Invitrogen Canada Inc.), purified, and quantified using the QubitQuant-iT™ assay and Qubit Fluorometer (Invitrogen Canada Inc.). An invitro transcription reaction was carried out using 100 ng of purifiedadapter-ligated DNA as per the manufacturer's specifications(Ampliscribe™ T7-Flash™ Biotin-RNA Transcription Kit; IntersciencesInc., Markham, Ont.). The reaction mixture was incubated at 37° C. for60 minutes, DNase-I treated for 15 minutes at 37° C., and then incubatedat 70° C. for 5 minutes to inactivate DNasel. Transcription productswere precipitated with 1 volume of 5M NH4Ac, and size fractioned on a10% Novex TBE-Urea gel (Invitrogen Canada Inc.). The 100 to 150 bpfraction was isolated from the gel, eluted into 0.3M NaCl, andEtOH-precipitated after extraction of the eluate from the gel slurry bycentrifugation through a Spin-X Filter centrifuge tube filter (FisherScientific Ltd.). The biotinylated RNA was resuspended in 20 μlnuclease-free water and quantified using an Agilent RNA Nano assay(Agilent Technologies Canada Inc.).

Indexed libraries of patient genomic DNA were pooled from 96 well platesin groups ranging from 36 to 47 libraries per pool [72]. A 250 to 350 bpsize fraction from each pool was size-selected by gel purification froman 8% Novex TBE gel as above (Invitrogen Canada Inc.). The protocoldescribed by Gnirke and colleagues [73] was followed for thehybridization reaction and subsequent washes, with an additionaloligonucleotide block consisting of standard Illumina PCR primers PE1and PE2 included in the hybridization reaction mixture to preventcross-hybridization between library fragments. The incubation of thelibrary fragments with the RNA probe pool was carried out for 24 hoursat 65° C., followed by binding to M-280 Streptavidin Dynabeads(Invitrogen Canada Inc.), washes, and elution of the captured libraryfragments. The eluted fragments were amplified by PCR using primers thatanneal upstream of the adapter index sites and subjected to clustergeneration and sequencing as described above.

Targeted MLL2 Resequencing Using Long-Range PCR and Sample Indexing

Due to the presence of inactivating mutations in different positionswithin the MLL2 gene, the entire MLL2 locus(chr12:47,699,025-47,735,374, hg18) was sequenced in a cohort of 35 FLand 37 DLBCL primary tumours, in 17 DLBCL derived cell lines and, as acontrol, in 8 centroblast samples. Genomic DNA from individual sampleswas normalized to 5 ng/μl, and 12.5 ng of each sample was PCR amplifiedusing LA Taq DNA polymerase (TaKaRa). Twelve long amplicons, of sizesranging from 6600 bp to 7800 bp, were obtained under the following PCRconditions: 94° C. for 5 minutes, 35 cycles of 98° C. for 10 seconds and68° C. for 8 minutes, and a final extension at 72° C. for 10 minutes.Amplicons were cleaned using AMPure beads (Beckman Coulter) and elutedwith 20-μL of TE. All 12 amplicons per sample were normalized and pooledtogether.

An individual indexed library was constructed from each sample(comprising the pool of the 12 long amplicons from MLL2). Approximately500 ng of each pooled DNA sample was sheared for 10 min using a SonicDismembrator 550 with a power setting of “7” in pulses of 30 secondsinterspersed with 30 seconds of cooling (Cup Horn, Fisher Scientific)and then analysed on 8% PAGE gels. The 200 to 300 bp DNA fraction wasexcised and eluted from the gel slice overnight at 4° C. in 300 μL ofelution buffer (5:1 (vol/vol) LoTE buffer (3 mM Tris-HCl, pH 7.5, 0.2 mMEDTA)/7.5 M ammonium acetate) and was purified using a Spin-X FilterTube (Fisher Scientific) and by ethanol precipitation. Indexed librarieswere prepared using a modified paired-end protocol. This involved DNAend-repair reactions at room temperature 20-25° C. for 30 minutes (5 UT4 DNA polymerase, 1 U Klenow DNA polymerase (exonuclease minus), 100 UT4 polynucleotide kinase and 0.4 mM dNTP mix (Invitrogen). End-repairreactions were purified using AMPure beads, and dATP was added to the 3′ends using 5 U Klenow DNA polymerase (exonuclease minus) and 0.2 mM dATPin 1× Klenow Buffer (Invitrogen) with 30-minute incubation at 37° C. ina Tetrad thermal cycler (MJ Research). DNA was again purified on AMPurebeads using a Biomek FX. Adapter ligation (10:1 ratio) was completedwith 0.03 μM adapter (multiplexing adapters 1 and 2), 100 ng DNA, 5 U T4DNA ligase, 0.2 mM ATP and 1×T4 DNA Ligase Buffer (Invitrogen) for 30minutes at room temperature. Adapter-ligated DNA was again purifiedusing AMPure beads on a Biomek FX. A selection of DNA samples werequantified on a Qubit (Invitrogen). 15-cycle indexing enrichment PCR wasperformed using Phusion DNA polymerase and Primers 1.0 and 2.0 (IDT) and96 custom indexing primers. PCR cycles were: 98° C. for 60 seconds,followed by 15 cycles of 98° C. for 10 seconds, 65° C. for 15 secondsand 72° C. for 30 seconds. The PCR products were purified using AMPurebeads and eluted in 40 μL elution buffer EB (Qiagen). Product qualitywas assessed by quality-control gels with 1.75% SeaKem LE agarose in1×TAE (0.2 μL of every amplicon) and on a 2100 Bioanalyzer (AgilentTechnologies).

Indexed libraries were pooled together and sequenced on two lanes of aflowcell using an Illumina GA_(II) platform. Individual indexes allowedthe deconvolution of reads deriving from individual samples inmultiplexed libraries such that many cases were concurrently sequencedin the same flow cell lane. The reads were matched to patient samplesusing the index read and were aligned with BWA to the human referencegenome (hg18). Point mutations were identified using SNVMix withstringent post-filtration including a requirement for dual-strandcoverage and requiring at least 10% of the aligned reads at a candidatevariant to be non-reference. Insertions and deletions were identifiedusing the SAMtools indel calling algorithm with similar filters. Onlyinsertions and deletions supported by at least 2 reads on each strandwere considered valid. The reported average coverage for each sample wascalculated as the average depth of aligned reads across each of thecoding (CDS) positions in the MLL2 locus.

Re-Confirmation of MLL2 Mutations in Patient Samples and DLBCL CellLines

MLL2 mutations found by targeted sequencing of MLL2 in lymphoma sampleswere validated by Sanger sequencing of the region surrounding eachmutation, except in 15 cases. To do so, primers were designed to amplify400-600 bp regions by PCR. Validating forward and reverse primerscarried T7 and M13Reverse 5′ tails, respectively. PCR conditions usedwere 94° C. for 2 minutes, 30 cycles of 94° C. for 30 seconds, 60° C.for 30 seconds and 72° C. for 1 minute, and a final extension at 72° C.for 8 minutes. To determine the somatic or germline origin of themutations, mutations were re-sequenced in both tumour and constitutionalDNA, the latter obtained from peripheral blood or negative sort cells.The sequencing reactions consisted of 50 cycles of 96° C. for 10 sec,43° C. (for M13Reverse) or 48° C. (T7) for 5 seconds and 60° C. for 4minutes and were analysed using an AB 3730XL. Variants were visuallyinspected to confirm their presence in tumour and absence from germlinetraces. In 8 of the patient samples that carried 2 mutations in MLL2, toestablish whether one allele contained both mutations or each allelecontained one, we sequenced both candidate mutations using DNA from BACclones from FL patient libraries. The primers and PCR conditions werethe same as those used for the validation of each of those mutations.

Targeted Resequencing of MEF2B Coding Exons 1 and 2

Coding exons 1 and 2 of MEF2B were PCR amplified using MEF2B_(—)1F/R andMEF2B_(—)2F/R primers using the same conditions for MLL2 (previousparagraph). Priming sites for T7 and M13Reverse were added to their 5′ends to allow direct Sanger sequencing of amplicons. Amplicons wereproduced from whole genome amplified tumour genomic DNA from lymphomapatients and DLBCL cell lines. Whole genome amplification was performedusing Repli-g Screening kit reagents (Qiagen), following themanufacturer instructions. All capillary traces were visually inspected.

Identification of Structural Aberrations Involving BCL2 and BCL6

The presence of translocations involving MYC, BCL2 and BCL6 wasdetermined for 49 of the DLBCL cases (FIG. 2) using commercial dualcolor “break-apart” probes from Abbott Molecular (Abbott Park, Ill.) onformalin fixed paraffin embedded tissue in tissue microarrays using thedescribed method [74]. Additional fusion transcripts involving BCL2 orBCL6 were detected in these and the remaining libraries directly fromthe RNA-seq data using both Trans-ABySS [48] and deFuse(http://compbio.bccrc.ca/?page_id=275).

Analysis of Impact of COO and Mutation Status on Outcome in DLBCL

The analysis included only patients treated with curative intent whoreceived at least one cycle of R-CHOP. Overall survival (OS) wascalculated as the time from date of diagnosis until death from anycause. Patients were censored at the time they were last known to bealive. OS was assessed using the Kaplan-Meier method and the log ranktest was used for comparison between groups. Data were analysed usingSPSS software (SPSS version 14.0 for Windows; SPSS Inc, Chicago, Ill.).

TABLE 1 Overview of cSNVs and confirmed somatic mutations in mostfrequently mutated genes. Somatic Skew cSNVs (M, WT, Cases Total(RNA-seq NS T both) Gene NS S T NS S T cohort)* P (raw) q SP SP ***MLL2^(†) 16 8 17 17 8 18 10 6.85 × 10 −8 8.50 × 10⁻⁷ 0.834 14.4 WTTNFRSF14^(G†) 7 1 7 8 1 7 11 6.85 × 10 −8 8.50 × 10⁻⁷ 7.52 118 bothSGK1^(G†) 18 6 6 37 10 6 9 6.85 × 10 −8 8.50 × 10⁻⁷ 19.5 61.7 —BCL10^(†) 2 0 4 3 0 4 4 6.85 × 10 −8 8.50 × 10⁻⁷ 3.62 112 WT GNA13^(G†)21 1 2 33 1 2 5 6.85 × 10 −8 8.50 × 10⁻⁷ 24.1 25.7 both TP53^(G†) 20 2 123 3 1 22 6.85 × 10 −8 8.50 × 10⁻⁷ 15.6 14.1 both EZH2^(G†) 33 0 0 33 00 33 6.85 × 10 −8 8.50 × 10⁻⁷ 11.4 0.00 both BTG2^(†) 12 6 1 14 6 1 26.85 × 10⁻⁸ 8.50 × 10⁻⁷ 23.9 35.1 — BCL2^(G†) 42 45 0 96 105 0 43 9.35 ×10 −8 8.50 × 10⁻⁷ 3.78 0.00 M BCL6^(†) ** 11 2 0 12 2 0 2 9.35 × 10 −88.50 × 10⁻⁷ 0.175 0.00 M CIITA^(†) ** 5 3 0 6 3 0 2 9.35 × 10 −8 8.50 ×10⁻⁷ 0.086 0.00 FAS^(†) 2 0 4 3 0 4 2 1.52 × 10⁻⁷ 1.17 × 10⁻⁶ 2.54 66.5WT BTG1^(†) 11 6 2 11 7 2 10 1.52 × 10⁻⁷ 1.17 × 10⁻⁶ 17.5 52.5 bothMEF2B^(G†) 20 2 0 20 2 0 in 2.05 × 10⁻⁷ 1.47 × 10⁻⁶ 14.2 0.00 M IRF8^(†)11 5 3 14 5 3 3 4.55 × 10⁻⁷ 3.03 × 10⁻⁶ 8.82 28.2 WT TMEM30A^(†) 1 0 4 10 4 4 6.06 × 10⁻⁷ 3.79 × 10⁻⁶ 0.785 65.0 WT CD58^(†) 2 0 3 2 0 3 2 2.42× 10⁻⁶ 1.43 × 10-⁻⁵ 2.29 69.2 — KLHL6^(†) 10 2 2 12 2 2 4 1.00 × 10⁻⁵5.26 × 10⁻⁵ 5.42 16.4 — MYD88^(A†) 13 2 0 14 2 0 9 1.00 × 10⁻⁵ 5.26 ×10⁻⁵ 12.4 0.00 WT CD70^(†) 5 0 1 5 0 2 3 1.70 × 10⁻⁵ 8.48 × 10⁻⁵ 7.0844.0 — CD79B^(A†) 7 2 1 9 2 1 5 2.00 × 10⁻⁵ 9.52 × 10⁻⁵ 10.9 18.3 MCCND3^(†) 7 1 2 7 1 2 6 2.80 × 10⁻⁵ 1.27 × 10⁻⁴ 6.55 36.3 WT CREBBP^(†)20 7 4 24 7 4 9 1.00 × 10⁻⁴ 4.35 × 10⁻⁴ 2.72 6.04 both HIST1H1C^(†) 9 00 10 0 0 6 1.80 × 10⁻⁴ 7.50 × 10⁻⁴ 11.9 0.00 both B2M^(†) 7 0 0 7 0 0 43.90 × 10⁻⁴ 1.56 × 10⁻³ 16.6 0.00 WT ETS1^(†) 10 1 0 10 1 0 4 4.10 ×10⁻⁴ 1.58 × 10⁻³ 5.76 0.00 WT CARD11^(†) 14 3 0 14 3 0 3 1.90 × 10⁻³7.04 × 10⁻³ 3.37 0.00 both FAT2^(†) ** 2 1 0 2 1 0 2 6.30 × 10⁻³ 2.25 ×10⁻² 0.128 0.00 — IRF4^(†) ** 9 4 0 26 5 0 5 7.00 × 10⁻³ 2.41 × 10⁻²0.569 0.00 both FOXO1^(†) 8 4 0 10 4 0 4 7.60 × 10⁻³ 2.53 × 10⁻² 4.020.00 — STAT3 9 0 0 9 0 0 4 2.19 × 10⁻² 6.08 × 10⁻² — — both RAPGEF1 8 30 10 3 0 3 2.98 × 10⁻² 7.45 × 10⁻² — — WT ABCA7 12 3 0 15 3 0 2 7.76 ×10⁻² 1.67 × 10⁻¹ — — WT RNE213 10 8 0 10 8 0 2 7.87 × 10⁻² 1.67 × 10⁻¹ —— — MUC16 17 12 0 39 25 0 2 8.32 × 10⁻² 1.73 × 10⁻¹ — — — HDAC7 8 4 0 84 0 2 8.94 × 10⁻² 1.82 × 10⁻¹ — — WT PRKDC 7 3 0 7 4 0 2 1.06 × 10⁻¹2.05 × 10⁻¹ — — — SAMD9 9 2 0 9 2 0 2 1.79 × 10⁻¹ 3.01 × 10⁻¹ — — — TAF110 0 0 10 0 0 2 3.03 × 10⁻¹ 4.74 × 10-1 — — — PIM1 20 19 0 33 34 0 113.40 × 10⁻¹ 5.23 × 10⁻¹ — — WT COL4A2 8 2 0 8 2 0 2 7.64 × 10⁻¹ 8.99 ×10⁻¹ — — — EP300 8 7 1 8 7 1 3 9.54 × 10⁻¹ 1.00 — — WT Individual caseswith nonsynonymous (NS), synonymous (S) and truncating (T) mutations andtotal number of mutations of each class is shown separately as somegenes contained multiple mutations in the same case. The P valuesindicated in bold are the upper limit on the P value for that genedetermined with the approach described by Greenman et al (see Methods)[19], q is the Benjamini-corrected q value, and NS, SP and T SP refer toselective pressure estimates from this model for the acquisition ofnonsynonymous or truncating mutations, respectively. ^(†)genessignificant at an FDR of 0.03. SNVs in BCL2 and previously confirmed hotspot mutations in EZH2 and CD79B are likely somatic in these samplesbased on published observations of others. * Additional somaticmutations identified in larger cohorts and insertion/deletion mutationsare not included in this total. ** Selective pressure estimates are both<1 indicating purifying selection rather than positive selection actingon this gene. *** “both” indicates we observed separate cases in whichskewed expression was seen but where this skew was not consistent forthe mutant or wild-type allele. Genes with a superscript of either A orG were found to have mutations significantly enriched in ABC or GCBcases, respectively (P<0.05, Fisher Exact test).

TABLE 2 Summary of types of MLL2 somatic mutations. Sample Type FL DLBCLDLBCL cell-line Centroblast Truncation 18 4 7 0 Indel with 22 8 6 0frameshift Splice site 4 2 0 0 SNV 3 2 2 0 Any mutation 31/35 12/3710/17 0/8 (number of cases) Percentage 89% 32% 59% 0%

TABLE 3 Mutations in selected B-cell NHL biomarkers from exome andgenome sequencing. Gene Detection Base Total cSNVs symbol Ensembl idmethod change Annotation in gene ABCA7 ENSG00000064687 genome G > AE1322K 13 ABCA7 ENSG00000064687 RNA-seq C > T S268L 13 B2MENSG00000166710 RNA-seq T > A Y86N 12 B2M ENSG00000166710 RNA-seq T > GM1R 12 B2M ENSG00000166710 RNA-seq A > T M1L 12 B2M ENSG00000166710genome T > A L12Q 12 BCL10 ENSG00000142867 genome A > C L225* 4 BCL10ENSG00000142867 genome T > A T229S 4 BCL10 ENSG00000142867 genome G > AS227L 4 BCL10 ENSG00000142867 RNA-seq G > C S136* 4 BCL10ENSG00000142867 RNA-seq T > A R135* 4 BCL10 ENSG00000142867 RNA-seq T >A K146* 4 BCL10 ENSG00000142867 RNA-seq T > A L225F 4 BCL2ENSG00000171791 exome C > T A2T 42 BCL2 ENSG00000171791 exome G > C H3D42 BCL2 ENSG00000171791 RNA-seq C > A R6I 42 BCL2 ENSG00000171791RNA-seq G > A P57S 42 BCL2 ENSG00000171791 RNA-seq C > T V35M 42 BCL2ENSG00000171791 RNA-seq A > C M16R 42 BCL2 ENSG00000171791 RNA-seq A > GF104L 42 BCL2 ENSG00000171791 RNA-seq G > A A131V 42 BCL2ENSG00000171791 RNA-seq C > T A61T 42 BCL2 ENSG00000171791 RNA-seq C > TA2T 42 BCL2 ENSG00000171791 RNA-seq T > A Y28F 42 BCL2 ENSG00000171791RNA-seq G > A A60V 42 BCL2 ENSG00000171791 RNA-seq G > A L86F 42 BCL2ENSG00000171791 RNA-seq A > G F49S 42 BCL2 ENSG00000171791 RNA-seq A > CH20Q 42 BCL2 ENSG00000171791 RNA-seq C > T R146K 42 BCL2 ENSG00000171791RNA-seq C > G E135D 42 BCL2 ENSG00000171791 RNA-seq C > T G47D 42 BCL2ENSG00000171791 RNA-seq T > A N11Y 42 BCL2 ENSG00000171791 RNA-seq C > TD31N 42 BCL2 ENSG00000171791 RNA-seq G > A A37V 42 BCL2 ENSG00000171791RNA-seq C > T R129H 42 BCL2 ENSG00000171791 RNA-seq T > C M16V 42 BCL2ENSG00000171791 RNA-seq G > A P59L 42 BCL2 ENSG00000171791 RNA-seq G > CL119V 42 BCL2 ENSG00000171791 RNA-seq A > T M16K 42 BCL2 ENSG00000171791RNA-seq T > A T125S 42 BCL2 ENSG00000171791 RNA-seq G > A T74I 42 BCL2ENSG00000171791 RNA-seq A > G S51P 42 BCL2 ENSG00000171791 RNA-seq C > AK17N 42 BCL2 ENSG00000171791 RNA-seq C > A G5V 42 BCL2 ENSG00000171791RNA-seq G > A P59S 42 BCL2 ENSG00000171791 RNA-seq G > C P57A 42 BCL2ENSG00000171791 RNA-seq T > C D34G 42 BCL2 ENSG00000171791 RNA-seq T > CI48V 42 BCL2 ENSG00000171791 RNA-seq G > C A60G 42 BCL2 ENSG00000171791RNA-seq G > C N11K 42 BCL2 ENSG00000171791 RNA-seq T > C T69A 42 BCL2ENSG00000171791 RNA-seq C > T A76T 42 BCL2 ENSG00000171791 RNA-seq G > AA60V 42 BCL2 ENSG00000171791 RNA-seq A > C H20Q 42 BCL2 ENSG00000171791RNA-seq A > C S167A 42 BCL2 ENSG00000171791 RNA-seq G > A T187I 42 BCL2ENSG00000171791 RNA-seq C > T S87N 42 BCL2 ENSG00000171791 RNA-seq A > TH20Q 42 BCL2 ENSG00000171791 RNA-seq C > G E13D 42 BCL2 ENSG00000171791RNA-seq A > G V156A 42 BCL2 ENSG00000171791 RNA-seq G > C F104L 42 BCL2ENSG00000171791 RNA-seq T > C N172S 42 BCL2 ENSG00000171791 RNA-seq A >G S50P 42 BCL2 ENSG00000171791 RNA-seq G > A P59L 42 BCL2ENSG00000171791 RNA-seq G > A P59S 42 BCL2 ENSG00000171791 RNA-seq C > AR107L 42 BCL2 ENSG00000171791 RNA-seq A > G Y21H 42 BCL2 ENSG00000171791RNA-seq T > C Q52R 42 BCL2 ENSG00000171791 RNA-seq G > C T7R 42 BCL2ENSG00000171791 RNA-seq C > T E165K 42 BCL2 ENSG00000171791 RNA-seq G >A A80V 42 BCL2 ENSG00000171791 RNA-seq C > T R146K 42 BCL2ENSG00000171791 RNA-seq A > G F49L 42 BCL2 ENSG00000171791 RNA-seq A > CF49C 42 BCL2 ENSG00000171791 RNA-seq C > G K17N 42 BCL2 ENSG00000171791RNA-seq G > A P65S 42 BCL2 ENSG00000171791 RNA-seq G > T A60D 42 BCL2ENSG00000171791 RNA-seq G > T S51Y 42 BCL2 ENSG00000171791 RNA-seq G > AP71S 42 BCL2 ENSG00000171791 RNA-seq G > A A43V 42 BCL2 ENSG00000171791RNA-seq G > A P59S 42 BCL2 ENSG00000171791 RNA-seq C > T G27D 42 BCL2ENSG00000171791 RNA-seq G > C A131G 42 BCL2 ENSG00000171791 RNA-seq C >T S87N 42 BCL2 ENSG00000171791 RNA-seq A > T L169Q 42 BCL2ENSG00000171791 RNA-seq G > A A131V 42 BCL2 ENSG00000171791 RNA-seq C >A A45S 42 BCL2 ENSG00000171791 RNA-seq C > T A60T 42 BCL2ENSG00000171791 RNA-seq T > G T69P 42 BCL2 ENSG00000171791 RNA-seq G > CS117R 42 BCL2 ENSG00000171791 RNA-seq A > G F49L 42 BCL2 ENSG00000171791RNA-seq C > T G47D 42 BCL2 ENSG00000171791 RNA-seq C > T V66I 42 BCL2ENSG00000171791 RNA-seq G > C P46A 42 BCL2 ENSG00000171791 RNA-seq G > AP59S 42 BCL2 ENSG00000171791 RNA-seq G > C P59A 42 BCL2 ENSG00000171791RNA-seq G > C P46A 42 BCL2 ENSG00000171791 RNA-seq G > A A131V 42 BCL2ENSG00000171791 RNA-seq T > A Y9F 42 BCL2 ENSG00000171791 RNA-seq A > GV159A 42 BCL2 ENSG00000171791 RNA-seq G > A T7I 42 BCL2 ENSG00000171791RNA-seq G > A P53S 42 BCL2 ENSG00000171791 RNA-seq G > C S87R 42 BCL2ENSG00000171791 RNA-seq G > T T7K 42 BCL2 ENSG00000171791 RNA-seq C > TR164Q 42 BCL2 ENSG00000171791 RNA-seq G > A T7I 42 BCL2 ENSG00000171791RNA-seq T > A I48F 42 BCL2 ENSG00000171791 RNA-seq T > C Y21C 42 BCL2ENSG00000171791 RNA-seq T > A T132S 42 BCL2 ENSG00000171791 RNA-seq T >C N143S 42 BCL2 ENSG00000171791 RNA-seq G > A A60V 42 BCL2ENSG00000171791 RNA-seq G > A A60V 42 BCL2 ENSG00000171791 RNA-seq T > GY108S 42 BCL6 ENSG00000113916 genome C > T A587T 11 BCL6 ENSG00000113916RNA-seq C > T A587T 11 BTG1 ENSG00000133639 genome G > C L94V 13 BTG1ENSG00000133639 RNA-seq G > A P58L 13 BTG1 ENSG00000133639 RNA-seq C > GQ36H 13 BTG1 ENSG00000133639 RNA-seq G > A H2Y 13 BTG1 ENSG00000133639RNA-seq C > G Q36H 13 BTG1 ENSG00000133639 RNA-seq A > T C149* 13 BTG1ENSG00000133639 RNA-seq C > T R27H 13 BTG1 ENSG00000133639 RNA-seq C > GA49P 13 BTG1 ENSG00000133639 RNA-seq G > C Q38E 13 BTG1 ENSG00000133639RNA-seq C > G E46D 13 BTG2 ENSG00000159388 RNA-seq C > A A45E 13 BTG2ENSG00000159388 RNA-seq G > A A45T 13 CARD11 ENSG00000198286 exome C > GE86Q; E93Q; E110Q 14 CARD11 ENSG00000198286 exome A > G L244P; L251P;L268P 14 CARD11 ENSG00000198286 RNA-seq T > C Q364R; Q371R; Q388R 14CARD11 ENSG00000198286 RNA-seq A > T M353K; M360K; M377K 14 CARD11ENSG00000198286 RNA-seq A > T F123I; F130I; F147I 14 CARD11ENSG00000198286 RNA-seq A > T F108I; F115I; F132I 14 CARD11ENSG00000198286 RNA-seq C > T D394N; D401N; D418N 14 CARD11ENSG00000198286 RNA-seq A > C Y333D; Y340D; Y357D 14 CARD11ENSG00000198286 RNA-seq A > C N230K; N237K; N254K 14 CARD11ENSG00000198286 RNA-seq C > T D223N; D230N; D247N 14 CARD11ENSG00000198286 RNA-seq T > G Q242P; Q249P; Q266P 14 CARD11ENSG00000198286 RNA-seq A > C F123C; F130C; F147C 14 CARD11ENSG00000198286 RNA-seq T > G Q242P; Q249P; Q266P 14 CARD11ENSG00000198286 RNA-seq C > T G116D; G123D; G140D 14 CCND3ENSG00000112576 RNA-seq G > A P234L; P280L; P284L 10 CCND3ENSG00000112576 RNA-seq G > A Q226*; Q272*; Q276* 10 CCND3ENSG00000112576 RNA-seq G > A Q226*; Q272*; Q276* 10 CCND3ENSG00000112576 RNA-seq A > C I240R; I286R; I290R 10 CCND3ENSG00000112576 RNA-seq A > T V237D; V283D; V287D 10 CCND3ENSG00000112576 RNA-seq T > G T233P; T279P; T283P 10 CD58ENSG00000116815 genome G > A Q141* 6 CD58 ENSG00000116815 RNA-seq C > AC131F 6 CD70 ENSG00000125726 exome A > C L60R 9 CD70 ENSG00000125726RNA-seq A > G F186S 9 CD70 ENSG00000125726 RNA-seq C > G G66R 9 CD79BENSG00000007312 RNA-seq T > G Y92S; Y196S; Y197S 8 CD79B ENSG00000007312RNA-seq A > G Y92H; Y196H; Y197H 8 CD79B ENSG00000007312 RNA-seq T > AY92F; Y196F; Y197F 8 CD79B ENSG00000007312 RNA-seq A > G Y92H; Y196H;Y197H 8 CD79B ENSG00000007312 RNA-seq T > C Y92C; Y196C; Y197C 8 CIITAENSG00000179583 exome A > T D748V; D777V 12 CIITA ENSG00000179583RNA-seq T > A L810Q; L839Q 12 COL4A2 ENSG00000134871 genome G > A G441D;G447D 8 COL4A2 ENSG00000134871 RNA-seq G > A G97E 8 CREBBPENSG00000005339 exome C > T E1012K; E1042K 23 CREBBP ENSG00000005339exome A > G Y71H; Y1482H; Y1512H 23 CREBBP ENSG00000005339 RNA-seq C > TS25N; S1436N; S1466N 23 CREBBP ENSG00000005339 RNA-seq A > T L88Q;L1499Q; L1529Q 23 CREBBP ENSG00000005339 RNA-seq A > G Y92H; Y1503H;Y1533H 23 CREBBP ENSG00000005339 RNA-seq G > C P77R; P1488R; P1518R 23CREBBP ENSG00000005339 RNA-seq A > G L88P; L1499P; L1529P 23 CREBBPENSG00000005339 RNA-seq G > A R35C; R1446C; R1476C 23 CREBBPENSG00000005339 RNA-seq A > T Y71N; Y1482N; Y1512N 23 CREBBPENSG00000005339 RNA-seq T > C M1625V; M1655V 23 CREBBP ENSG00000005339genome G > A Q1104*; Q1134* 23 EP300 ENSG00000100393 RNA-seq T > AY1467N 10 EP300 ENSG00000100393 RNA-seq T > C Y1467H 10 EP300ENSG00000100393 RNA-seq G > A A1498T 10 EP300 ENSG00000100393 genome T >C L415P 10 ETS1 ENSG00000134954 RNA-seq G > A L23F 12 ETS1ENSG00000134954 RNA-seq G > A L23F 12 ETS1 ENSG00000134954 RNA-seq C > GE22D 12 ETS1 ENSG00000134954 RNA-seq T > C M1V 12 ETS1 ENSG00000134954genome G > C T12S 12 EZH2 ENSG00000106462 genome G > C A638G; A682G 33EZH2 ENSG00000106462 RNA-seq G > A A648V; A692V 33 EZH2 ENSG00000106462exome T > G Y602S; Y646S 33 EZH2 ENSG00000106462 genome T > A Y602F;Y646F 33 EZH2 ENSG00000106462 exome A > G Y602H; Y646H 33 EZH2ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2 ENSG00000106462RNA-seq T > G Y602S; Y646S 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N;Y646N 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N; Y646N 33 EZH2ENSG00000106462 RNA-seq A > T Y602N; Y646N 33 EZH2 ENSG00000106462RNA-seq A > T Y602N; Y646N 33 EZH2 ENSG00000106462 RNA-seq A > G Y602H;Y646H 33 EZH2 ENSG00000106462 RNA-seq A > G Y602H; Y646H 33 EZH2ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2 ENSG00000106462RNA-seq A > G Y602H; Y646H 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N;Y646N 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N; Y646N 33 EZH2ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2 ENSG00000106462RNA-seq T > G Y602S; Y646S 33 EZH2 ENSG00000106462 RNA-seq A > G Y602H;Y646H 33 EZH2 ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2ENSG00000106462 RNA-seq A > G Y602H; Y646H 33 EZH2 ENSG00000106462RNA-seq A > T Y602N; Y646N 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N;Y646N 33 EZH2 ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2ENSG00000106462 RNA-seq T > G Y602S; Y646S 33 EZH2 ENSG00000106462RNA-seq A > T Y602N; Y646N 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N;Y646N 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N; Y646N 33 EZH2ENSG00000106462 RNA-seq T > A Y602F; Y646F 33 EZH2 ENSG00000106462RNA-seq A > T Y602N; Y646N 33 EZH2 ENSG00000106462 RNA-seq T > A Y602F;Y646F 33 EZH2 ENSG00000106462 RNA-seq A > T Y602N; Y646N 33 FASENSG00000026103 exome C > T Q255*; Q276*; Q303* 6 FAS ENSG00000026103RNA-seq T > G Y211*; Y232*; Y259* 6 FAS ENSG00000026103 genome G > CV224L; V245L; V272L 6 FAS ENSG00000026103 genome A > G D244G; D265G;D292G 6 FAT2 ENSG00000086570 exome C > T D1287N 2 FAT2 ENSG00000086570exome C > T G994R 2 FOXO1 ENSG00000150907 RNA-seq C > T S203N 10 FOXO1ENSG00000150907 RNA-seq T > C M1V 10 FOXO1 ENSG00000150907 RNA-seq G > AT24I 10 FOXO1 ENSG00000150907 RNA-seq G > T S193R 10 FOXO1ENSG00000150907 RNA-seq T > C T24A 10 GNA13 ENSG00000120063 RNA-seq G >A L296F 22 GNA13 ENSG00000120063 RNA-seq T > C K292R 22 GNA13ENSG00000120063 RNA-seq T > C T262A 22 GNA13 ENSG00000120063 RNA-seq A >G *378R 22 GNA13 ENSG00000120063 RNA-seq T > A K42* 22 GNA13ENSG00000120063 RNA-seq T > G H345P 22 GNA13 ENSG00000120063 RNA-seq T >C T203A 22 GNA13 ENSG00000120063 RNA-seq G > A S31F 22 GNA13ENSG00000120063 genome A > T I158K 22 HDAC7 ENSG00000061273 genome G > AS155F; S194F 9 HDAC7 ENSG00000061273 RNA-seq C > T A786T; A788T; A825T 9HIST1H1C ENSG00000187837 genome G > C A185G 10 HIST1H1C ENSG00000187837genome C > G A180P 10 HIST1H1C ENSG00000187837 RNA-seq G > A P118S 10HIST1H1C ENSG00000187837 RNA-seq C > G V132L 10 HIST1H1C ENSG00000187837RNA-seq G > C L107V 10 HIST1H1C ENSG00000187837 RNA-seq C > T E74K 10HIST1H1C ENSG00000187837 genome C > G G103A 10 IKZF3 ENSG00000161405RNA-seq T > G N73T; N160T 7 IRF4 ENSG00000137265 RNA-seq G > C S18T 9IRF4 ENSG00000137265 RNA-seq C > G L40V 9 IRF4 ENSG00000137265 RNA-seqA > G I32V 9 IRF4 ENSG00000137265 RNA-seq A > G N2S 9 IRF4ENSG00000137265 RNA-seq C > A Q60K 9 IRF4 ENSG00000137265 RNA-seq C > GS18R 9 IRF4 ENSG00000137265 RNA-seq G > C Q60H 9 IRF4 ENSG00000137265RNA-seq A > C S48R 9 IRF4 ENSG00000137265 RNA-seq C > A S48R 9 IRF8ENSG00000140968 genome T > G S55A 14 IRF8 ENSG00000140968 genome G > CS34T 14 IRF8 ENSG00000140968 RNA-seq A > T *427L 14 KLHL6ENSG00000172578 genome C > G S83T; S94T 13 KLHL6 ENSG00000172578 RNA-seqG > C T53S; T64S 13 KLHL6 ENSG00000172578 RNA-seq A > T L45*; L56* 13KLHL6 ENSG00000172578 RNA-seq G > A T53I; T64I 13 KLHL6 ENSG00000172578RNA-seq G > C L54V; L65V 13 MEF2B ENSG00000064489 exome T > C Y69C 20MEF2B ENSG00000064489 RNA-seq T > A D83V 20 MEF2B ENSG00000064489RNA-seq T > A D83V 20 MEF2B ENSG00000064489 RNA-seq T > A D83V 20 MEF2BENSG00000064489 RNA-seq A > C L67R 20 MEF2B ENSG00000064489 RNA-seq A >G Y69H 20 MEF2B ENSG00000064489 RNA-seq T > A D83V 20 MEF2BENSG00000064489 RNA-seq T > G D83A 20 MEF2B ENSG00000064489 RNA-seq T >A N81Y 20 MEF2B ENSG00000064489 genome G > T N81K 20 MLL2ENSG00000167548 genome G > A Q3391* 29 MLL2 ENSG00000167548 RNA-seq C >G A4607P 29 MLL2 ENSG00000167548 RNA-seq C > T R2547H 29 MLL2ENSG00000167548 RNA-seq G > A R2250* 29 MLL2 ENSG00000167548 RNA-seq G >A P3583S 29 MLL2 ENSG00000167548 RNA-seq G > A R4634C 29 MLL2ENSG00000167548 RNA-seq G > A R3956* 29 MLL2 ENSG00000167548 RNA-seq G >A Q3333* 29 MLL2 ENSG00000167548 RNA-seq G > A R4921* 29 MLL2ENSG00000167548 RNA-seq G > A R2107* 29 MLL2 ENSG00000167548 genome G >A Q3394* 29 MUC16 ENSG00000181143 genome A > G S2928P 17 MUC16ENSG00000181143 genome T > G S1055R 17 MUC16 ENSG00000181143 genome G >T S464Y; S2725Y; S4093Y; S8460Y 17 MYD88 ENSG00000172936 RNA-seq C > GS206C 14 MYD88 ENSG00000172936 RNA-seq T > C L252P 14 MYD88ENSG00000172936 RNA-seq T > C L252P 14 MYD88 ENSG00000172936 RNA-seq T >C L252P 14 MYD88 ENSG00000172936 RNA-seq T > C L252P 14 MYD88ENSG00000172936 RNA-seq T > C L252P 14 MYD88 ENSG00000172936 RNA-seq C >G S206C 14 MYD88 ENSG00000172936 RNA-seq G > A S230N 14 MYD88ENSG00000172936 genome G > A S230N 14 PIM1 ENSG00000137193 RNA-seq C > GL164V; L255V 21 PIM1 ENSG00000137193 RNA-seq C > G L164V; L255V 21 PIM1ENSG00000137193 RNA-seq C > G L25V; L116V 21 PIM1 ENSG00000137193RNA-seq C > T L164F; L255F 21 PIM1 ENSG00000137193 RNA-seq G > C E181D;E272D 21 PIM1 ENSG00000137193 RNA-seq G > A S97N; S188N 21 PIM1ENSG00000137193 RNA-seq G > A S97N; S188N 21 PIM1 ENSG00000137193RNA-seq G > C E79D; E170D 21 PIM1 ENSG00000137193 RNA-seq G > C K24N;K115N 21 PIM1 ENSG00000137193 RNA-seq C > G S146R; S237R 21 PIM1ENSG00000137193 RNA-seq G > C Q37H; Q128H 21 PIM1 ENSG00000137193RNA-seq C > G S146R; S237R 21 PIM1 ENSG00000137193 RNA-seq C > T L2F;L93F 21 PIM1 ENSG00000137193 RNA-seq C > G L2V; L93V 21 PIM1ENSG00000137193 RNA-seq G > C Q37H; Q128H 21 PLCG2 ENSG00000197943 exomeC > A S16R 7 PRKDC ENSG00000121031 genome A > C F1854V 7 PRKDCENSG00000121031 RNA-seq A > C F3973V; F4004V 7 RAPGEF1 ENSG00000107263RNA-seq C > T S53N; S284N; S358N; S375N; S376N 8 RAPGEF1 ENSG00000107263RNA-seq A > T Y265N; Y496N; Y570N; Y587N; Y588N 8 RAPGEF1ENSG00000107263 RNA-seq C > G V16L; V297L; V528L; V602L; V619L; V620L 8RAPGEF1 ENSG00000107263 genome A > T M250K; M481K; M555K; M572K; M573K 8RFTN1 ENSG00000131378 exome C > A S224I 6 RFTN1 ENSG00000131378 RNA-seqG > A P205S 6 RNF213 ENSG00000173821 genome T > A N2194K 11 RNF213ENSG00000173821 RNA-seq G > A R2286Q 11 SAMD9 ENSG00000205413 genome T >A N615Y 11 SAMD9 ENSG00000205413 RNA-seq A > G I1578T 11 SGK1ENSG00000118515 exome C > G A105P; A115P; A129P; A210P 20 SGK1ENSG00000118515 RNA-seq T > C R21G; R31G; R45G; R126G 20 SGK1ENSG00000118515 RNA-seq G > T A115E; A125E; A139E; A220E 20 SGK1ENSG00000118515 RNA-seq G > T H153Q; H163Q; H177Q; H258Q 20 SGK1ENSG00000118515 RNA-seq G > C A193G; A203G; A217G; A298G 20 SGK1ENSG00000118515 RNA-seq A > T N34K; N44K; N58K; N139K 20 SGK1ENSG00000118515 RNA-seq G > C F113L; F123L; F137L; F218L 20 SGK1ENSG00000118515 RNA-seq C > G S242T; S252T; S266T; S347T 20 SGK1ENSG00000118515 RNA-seq G > A P67S; P77S; P91S; P172S 20 SGK1ENSG00000118515 RNA-seq T > A K19M; K29M; K43M; K124M 20 SGK1ENSG00000118515 RNA-seq G > A Q30*; Q40*; Q54*; Q135* 20 SGK1ENSG00000118515 RNA-seq G > A T5I 20 SGK1 ENSG00000118515 RNA-seq C > AE136*; E146*; E160*; E241* 20 SGK1 ENSG00000118515 RNA-seq G > A P65S;P75S; P89S; P170S 20 SGK1 ENSG00000118515 RNA-seq G > A P63S; P73S;P87S; P168S 20 SGK1 ENSG00000118515 RNA-seq C > A R22M; R32M; R46M;R127M 20 SGK1 ENSG00000118515 RNA-seq G > T T229N; T239N; T253N; T334N20 SGK1 ENSG00000118515 RNA-seq C > G R211T; R221T; R235T; R316T 20 SGK1ENSG00000118515 genome C > T C183Y; C193Y; C207Y; C288Y 20 SGK1ENSG00000118515 genome G > T R6S 20 SGK1 ENSG00000118515 genome C > AE338*; E348*; E362*; E443* 20 SGK1 ENSG00000118515 genome G > A P81L;P91L; P105L; P186L 20 SGK1 ENSG00000118515 genome G > A P11L 20 STAT3ENSG00000168610 exome G > C S614R 9 STAT3 ENSG00000168610 RNA-seq A > TN567K 9 STAT3 ENSG00000168610 RNA-seq C > T E616K 9 STAT3ENSG00000168610 RNA-seq C > T D566N 9 STAT6 ENSG00000166888 exome G > TQ286K 6 STAT6 ENSG00000166888 RNA-seq T > C D419G 6 TAF1 ENSG00000147133genome T > C L1000P; L1021P 10 TAF1 ENSG00000147133 RNA-seq T > CF1047S; F1068S 10 TMEM30A ENSG00000112697 genome A > T D155E; D191E 4TMEM30A ENSG00000112697 genome A > C Y157*; Y193* 4 TMEM30AENSG00000112697 RNA-seq G > T S280*; S316* 4 TMEM30A ENSG00000112697RNA-seq G > A R254*; R290* 4 TMEM30A ENSG00000112697 RNA-seq C > TW281*; W317* 4 TNFRSF14 ENSG00000157873 RNA-seq C > T W12* 14 TNFRSF14ENSG00000157873 RNA-seq G > T C57* 14 TNFRSF14 ENSG00000157873 RNA-seqG > C S112C 14 TNFRSF14 ENSG00000157873 RNA-seq C > T W201* 14 TNFRSF14ENSG00000157873 RNA-seq T > A N110Y 14 TNFRSF14 ENSG00000157873 RNA-seqC > T W12* 14 TNFRSF14 ENSG00000157873 RNA-seq G > A Q95* 14 TNFRSF14ENSG00000157873 RNA-seq A > G C53R 14 TNFRSF14 ENSG00000157873 RNA-seqG > T Y47* 14 TNFRSF14 ENSG00000157873 genome C > T W7* 14 TNFRSF14ENSG00000157873 genome C > T G60D 14 TP53 ENSG00000141510 RNA-seq C > TV50M; V143M 21 TP53 ENSG00000141510 RNA-seq A > C C83G; C176G 21 TP53ENSG00000141510 RNA-seq T > C Y127C; Y220C 21 TP53 ENSG00000141510RNA-seq A > T Y112N; Y205N 21 TP53 ENSG00000141510 RNA-seq A > C Y107D21 TP53 ENSG00000141510 RNA-seq T > C Y141C; Y234C 21 TP53ENSG00000141510 RNA-seq A > T Y141N; Y234N 21 TP53 ENSG00000141510RNA-seq G > A R155W; R248W 21 TP53 ENSG00000141510 RNA-seq A > C Y107D21 TP53 ENSG00000141510 RNA-seq A > C S122R; S215R 21 TP53ENSG00000141510 RNA-seq A > C Y107D 21 TP53 ENSG00000141510 RNA-seq G >A R155W; R248W 21 TP53 ENSG00000141510 RNA-seq C > A G262V 21 TP53ENSG00000141510 RNA-seq A > G F41L; F134L 21 TP53 ENSG00000141510RNA-seq C > T R65H; R158H 21 TP53 ENSG00000141510 RNA-seq A > C Y33D;Y126D 21 TP53 ENSG00000141510 RNA-seq C > T G152D; G245D 21 TP53ENSG00000141510 RNA-seq T > C T18A 21 TP53 ENSG00000141510 RNA-seq C > AC83F; C176F 21 TP53 ENSG00000141510 RNA-seq T > A K319* 21 TP53ENSG00000141510 RNA-seq G > A R155W; R248W 21 TP53 ENSG00000141510RNA-seq T > C Y141C; Y234C 21 TP53 ENSG00000141510 RNA-seq T > A I255F21 TP53 ENSG00000141510 RNA-seq G > A P278L 21 TP53 ENSG00000141510RNA-seq T > A M144L; M237L 21

TABLE 4 Mutation hotspots in genes identified using RNA-seq. Number ofDistinct Codon Samples mutations Gene Name 602; 646 30 4 EZH2 83^(§) 9 2MEF2B 69^(§) 4 2 MEF2B 81^(§) 2 2 MEF2B 1482^(§)  3 2 CREBBP 1499^(§)  22 CREBBP 1467^(§)  2 2 EP300 287^(§)  2 1 HLA-C 1 8 5 BCL7A ^(‡)206^(§)  4 1 MYD88 ^(‡) 230^(§)  2 1 MYD88 ^(‡) 252^(§)  6 1 MYD88 ^(‡)59  7 3 BCL2* 92; 196; 197 5 4 CD79B ^(‡)   73; 160^(§) 4 2 IKZF3^(‡) 164; 255^(§) 3 2 PIM1 ^(‡)  97; 188 3 2 PIM1 ^(‡) 18^(§) 3 2 IRF4 ^(‡)587^(§)  3 2 BCL6 45^(§) 3 2 BTG2^(‡) 141; 234 3 2 TP53 ^(‡) 24^(§) 2 2FOXO7^(‡)  1^(§) 3 3 FOXO1^(‡) 12^(§) 2 1 TNFRSF14 226^(§)  2 2CCND3^(‡) 233^(§)  2 2 CCND3^(‡)  1^(§) 3 3 B2M^(‡) ^(§)This mutationwas proven to be somatic in at least one case; that is, present intumour DNA but absent in matched constitutional DNA. ^(‡)Not mutated inany of the fourteen genomes or exomes sequenced. *Additional hot spotsin BCL2 were excluded to simplify the table. Genes indicated in bold arepreviously described targets of somatic mutation in lymphoma. Althoughknown to be mutated, hot spots have not, to our knowledge, beendescribed in BCL7A. Note that Tyr641 as previously described [13] isbased on the Uniprot sequence Q15910, whereas this site corresponds toresidue 602 and 646 in the Refseq annotations.

TABLE 5 Mutations affecting CREBBP or EP300 detected using RNA-seq data.EP300 Library Disease Gene Annotation position HS0841 DLBCL CREBBPE1238*; E1268* E1202 line HS0842 DLBCL CREBBP A436V A420 line HS0842DLBCL CREBBP Q170*; Q238* not line conserved HS0806 FL CREBBP Y71H;Y1482H; Y1512H^(§) Y1446 HS1185 FL CREBBP G1411E; G1441E G1375 HS1200 FLCREBBP Y92F; Y1503F; Y1533F Y1467 HS1360 FL CREBBP R35C; R1446C; R1476CR1410 HS1361 FL CREBBP S25N; S1436N; S1466N^(§) S1400 HS0637 DLBCLCREBBP Q1104*; Q1134* Q1068 HS0641 DLBCL CREBBP L88Q; L1499Q; L1529Q^(§)L1463 HS0649 DLBCL CREBBP P77R; P1488R; P1518R^(§) P1452 HS0649 DLBCLCREBBP A687V; A717V not conserved HS0749 DLBCL CREBBP N1589K; N1619KN1552 HS0933 DLBCL CREBBP R370*; R438* R354 HS0939 DLBCL CREBBP M1625V;M1655V^(§) M1588 HS1135 DLBCL CREBBP V1342E; V1372E V1306 HS1460 DLBCLCREBBP L88P; L1499P; L1529P^(§) L1463 HS1977 DLBCL CREBBP C1283R; C1313RC1247 HS1979 DLBCL CREBBP N513S; N1978S; N2008S not conserved HS2059DLBCL CREBBP Y71N; Y1482N; Y1512N^(§) Y1446 HS2249 DLBCL CREBBP A442T;A1907T; A1937T not conserved HS2249 DLBCL CREBBP Y92H; Y1503H;Y1533H^(§) Y1467 HS2606 DLBCL CREBBP R35C; R1446C; R1476C^(§) R1410HS0653 DLBCL EP300 Q1904* — HS0939 DLBCL EP300 A1498T^(§) — HS1133 DLBCLEP300 L415P — HS1462 DLBCL EP300 Y1467H ^(§) — HS2049 DLBCL EP300P925T^(‡) — HS2607 DLBCL EP300 P925T^(‡) — HS1199 FL EP300 D1485V —HS1201 FL EP300 Q1455L — HS1202 FL EP300 Y1467N ^(§) — HS0841 DLBCLEP300 Q160* — line HS0900 DLBCL EP300 R1627W — line ^(§)mutation wasproven to be somatic (absent in matched constitutional DNA); ^(‡)wasalso found in the matched constitutional DNA (inherited variant); boldindicates mutation hot spots.

TABLE 6 Mutations in MLL2 found by targeted MLL2 resequencing.Chromosome Somatic locus Mutation Event Lymphoma status chr12: 47731299GAG > TAG E812* FL somatic chr12: 47720827 −A Frameshift deletion FLsomatic chr12: 47731577 −GCTGGAGGAGTCACCC Frameshift deletion FL somaticchr12: 47719922 TCA > TAA S2633* FL somatic chr12: 47728117 −ATFrameshift deletion FL somatic chr12: 47718602 TCA > TGA S2935* FLsomatic chr12: 47706246 GAC > GTC D5257V_FYRC domain FL somaticchr12: 47706727 CGA > TGA R5097* FL somatic chr12: 47719661 CGA > TGAR2685* FL somatic chr12: 47731461 GAG > TAG E758* FL somaticchr12: 47733524 T > C SS end6 FL somatic chr12: 47729734 CAG > TAGQ1302* FL somatic chr12: 47719040 G > A SS beg34 FL somaticchr12: 47721300 CAG > TAG Q2174* FL somatic chr12: 47728117 −ATFrameshift deletion FL somatic chr12: 47707855 CAG > TAG Q4881* FLsomatic chr12: 47718680 −AAGT Frameshift deletion FL somaticchr12: 47717409 CAG > TAG Q3333* FL somatic chr12: 47724315 −CAFrameshift deletion  FL somatic ++ chr12: 47711008 CGA > TGA R4536* FLsomatic chr12: 47734195 −GCAGCGCTG Frameshift deletion FL somatic(SSbeg5) chr12: 47711624 TGG > TGA W4377* FL somatic chr12: 47719271 G >A SS end33 FL somatic chr12: 47718918 CGA > TGA R2830* FL somaticchr12: 47713018 CAG > TAG Q3913* FL somatic chr12: 47720103 −GFrameshift deletion  FL somatic ++ chr12: 47702684 CGG > TGGR5432W_SET domain FL somatic chr12: 47713509 −ACAG Frameshift deletionFL somatic chr12: 47731159 +T Frameshift insertion FL somaticchr12: 47717445 CGA > TGA R3321* FL somatic chr12: 47709482 +ATFrameshift insertion FL somatic chr12: 47714889 −G + TAFrameshift in-del FL somatic chr12: 47717767 +T Frameshift deletion FLsomatic chr12: 47722866 CGA > TGA R1903* FL somatic chr12: 47720228 −CFrameshift deletion FL somatic chr12: 47704937 CGA > TGA R5282* FLundetermined chr12: 47726475 G > A SS beg16 FL undeterminedchr12: 47702165 −CG + T Frameshift deletion  FL undetermined in-delchr12: 47713960 CAG > TAG Q3599* FL undetermined chr12: 47713064 +TFrameshift insertion FL undetermined chr12: 47723788 −CFrameshift deletion FL undetermined chr12: 47704873 CGC > CACR5303H_FYRC domain FL undetermined chr12: 47719320 +CGACTCTFrameshift insertion FL undetermined chr12: 47702170 −TGFrameshift deletion FL undetermined chr12: 47718081 +GFrameshift insertion FL undetermined chr12: 47704646 +GFrameshift insertion FL undetermined chr12: 47714203 +AFrameshift insertion FL undetermined chr12: 47718680 −AAGTFrameshift deletion GCB-DLBCL somatic chr12: 47726113 T > G SS end17GCB-DLBCL somatic chr12: 47730448 +G Frameshift insertion GCB-DLBCLsomatic chr12: 47724460 TAT > TAA Y1692* GCB-DLBCL somaticchr12: 47712844 CAA > TAA Q3971* GCB-DLBCL somatic chr12: 47724319 −AFrameshift deletion ABC-DLBCL somatic chr12: 47706936 CGA > CAAR5027L_FYRC domain GCB-DLBCL somatic chr12: 47723144 −ACAGFrameshift deletion GCB-DLBCL undetermined chr12: 47710329 G > ASS end42 GCB-DLBCL undetermined chr12: 47719628 CAG > TAG Q2696*GCB-DLBCL somatic chr12: 47732160 −AG Frameshift deletion GCB-DLBCLundetermined chr12: 47718251 −TA Frameshift deletion GCB-DLBCL somaticchr12: 47719327 CGA > TGA R2771* ABC-DLBCL somatic chr12: 47710444 +CFrameshift insertion ABC-DLBCL undetermined chr12: 47709214 −GFrameshift deletion GCB-DLBCL somatic chr12: 47733683 CGC > GGCR228G_PHD domain GCB-DLBCL undetermined chr12: 47719508 CAG > TAG Q2736*GCB-DLBCLcl cell line chr12: 47732295 −C Frameshift deletion GCB-DLBCLclcell line chr12: 47717574 CAA > TAA Q3278* GCB-DLBCLcl cell linechr12: 47717760 GAG > TAG E3216* ABC-DLBCLcl cell line chr12: 47720598+A Frameshift insertion ABC-DLBCLcl cell line chr12: 47702767 TCC > TTCS5404F_SET domain GBC-DLBCLcl cell line chr12: 47712865 CAG > TAG Q3964*ABC-DLBCLcl cell line chr12: 47729996 −G Frameshift deletion ABC-DLBCLclcell line chr12: 47722866 CGA > TGA A1903* GBC-DLBCLcl cell linechr12: 47707230 −C Frameshift deletion GBC-DLBCLcl cell linechr12: 47717493 −GTTTGGCTGGGTCCCA Frameshift deletion  GBC-DLBCLclcell line ++ chr12: 47734070 CAG > TAG Q211* GCB-DLBCLcl cell linechr12: 47709228 GAG > TAG E4712* GBC-DLBCLcl cell line chr12: 47731793+C Frameshift  ABC-DLBCLcl cell line insertion ++ chr12: 47706741 TGC >TAC C5092Y_PHD domain GBC-DLBCLcl cell lineAdditional mutations at splice sites in MLL2 detected by Trans-ABySSchr12: 47733693 T > G SS end38 DLBCL n/a chr12: 47714115 T > G SS beg6DLBCL n/a ++ homozygous mutations; SS Splice site mutations; *notdetected by RNA-seq automated analysis; **indels and mutations at splicesites were not part of our automated analysis of RNA-seq; n/a refers tosamples for which either RNA-seq or targeted resequencing was notperformed.

TABLE 7 All MEF2B mutations detected. Case Position Change ChangeDiagnosis and subtype (res_id) (chromosome) (DNA) (protein)(subtyping method) 03-31934 chr19: 19122543 T > A M1K FL 02-17440chr19: 19122535 A > G K4E GCB DLBCL (GEP) 98-17403 chr19: 19122535 A > GK4E DLBCL 06-20044 chr19: 19122535^(§) A > G K4E FL 06-23741chr19: 19122535^(§) A > G K4E FL 07-14540 chr19: 19122535 A > G K4E FL98-14740 chr19: 19122535 A > G K4E FL 05-15463 chr19: 19122532 A > G K5EFL 03-28045 chr19: 19122523 A > G I8V DLBCL 92-59893 chr19: 19122502 A >G R15G DLBCL 02-28712 chr19: 19122492 C > T Q18* DLBCL 05-22052chr19: 19121225 A > G K23R DLBCL 07-10201 chr19: 19121222 G > A R24Q FLSPEC1187 chr19: 19121217 T > G F26V GCB DLBCL (GEP) 06-20952chr19: 19121195 A > C Y33S FL 03-18669 chr19: 19121153 T > C I47T DLBCL03-33888 chr19: 19121135 G > A R53H DLBCL 01-16433 chr19: 19121093^(§)T > G L67R FL 00-15694 chr19: 19121088^(§) A > G Y69H GCB DLBCL (GEP)05-11328 chr19: 19121088 A > G Y69H GCB DLBCL (GEP) 06-12968chr19: 19121087^(§) T > C Y69C FL 06-18193 chr19: 19121087 T > C Y69C FL08-10448 chr19: 19121087 T > C Y69C FL 99-30068 chr19: 19121087 T > CY69C FL 05-11369 chr19: 19121066 −GGGGCT E74-P75- FL H76 > D 06-23851chr19: 19121066 A > G H76R FL 07-21828 chr19: 19121064 G > A E77K DLBCL07-30109 chr19: 19121063 A > G E77G Composite FL 06-30145chr19: 19121052^(§) A > T N81Y GCB DLBCL (GEP) 05-23110chr19: 19121050^(§) C > A N81K GCB DLBCL (GEP) 00-13940 chr19: 19121045T > G D83A GCB DLBCL (IHC) 06-15922 chr19: 19121045^(§) T > G D83AGCB DLBCL (GEP) 07-23804 chr19: 19121045 T > G D83A GCB DLBCL (GEP)00-22287 chr19: 19121045 T > A D83V GCB DLBCL (IHC) 01-18672chr19: 19121045 T > A D83V GCB DLBCL (IHC) 02-30647 chr19: 19121045^(§)T > A D83V GCB DLBCL (GEP) 03-11110 chr19: 19121045 T > A D83V DLBCL03-26817 chr19: 19121045 T > A D83V GCB DLBCL (GEP) 03-30438chr19: 19121045 T > A D83V GCB DLBCL (GEP) 05-24666 chr19: 19121045 T >A D83V GCB DLBCL (GEP) 06-30025 chr19: 19121045^(§) T > A D83VGCB DLBCL (GEP) 06-33777 chr19: 19121045^(§) T > A D83V GCB DLBCL (GEP)78-60284 chr19: 19121045 T > A D83V GCB DLBCL (IHC) 95-32814chr19: 19121045^(§) T > A D83V GCB DLBCL (GEP) 97-10270 chr19: 19121045T > A D83V DLBCL DB (cell line) chr19: 19121045 T > A D83VGCB DLBCL (GEP) 06-11109 chr19: 19121045 T > G D83A FL 07-20462chr19: 19121045 T > G D83A FL 91-34915 chr19: 19121045 T > G D83A FL03-16286 chr19: 19121045 T > C D83G FL 05-12024 chr19: 19121045 T > AD83V FL 06-22766 chr19: 19121045 T > A D83V FL 06-33903 chr19: 19121045T > A D83V FL 89-30159 chr19: 19121045 T > A D83V FL 91-53679chr19: 19121045 T > A D83V FL 97-23234 chr19: 19121045 T > A D83V FL99-21548 chr19: 19121045 T > A D83V FL 01-24821 chr19: 19119600 +A L100FL Frameshift 85-31959 chr19: 19119578 C > A E108* FL 06-16716chr19: 19119559^(‡) C > T R114Q ABC DLBCL (GEP) 02-18484 chr19: 1911953910 bp  G121 FL del Frameshift 91-53679 chr19: 19118877 −GGAA F170 FLFrameshift 08-15460 chr19: 19118875 −AAGG P169 DLBCL Frameshift 06-10398chr19: 19118406 +GG G242 ABC DLBCL (GEP) Frameshift 06-30389chr19: 19118365 −C P256 FL Frameshift 07-18609 chr19: 19117831 A > CS294R† FL 05-20543 chr19: 19117794 G > T R307S† ABC DLBCL (GEP) 05-14545chr19: 19117608 A > G *369G† FL 06-23851 chr19: 19117608 A > C *369E† FL06-12557 chr19: 19117606 C > G *369Y† FL †annotation is unique toNM_001145785, representing the longest MEF2B isoform; ^(§)was proven tobe somatic (absent in matched constitutional DNA); ^(‡)was also found inthe matched constitutional DNA (inherited variant).

TABLE 8 Catalogue of MEF2B cSNVs in FL and DLBCL. Amino Acid Change FLDLBCL Total % variants M1K 1 0 1 1.4 K4E^(§) 4 2 6 8.7 K5E 1 0 1 1.4 I8V0 1 1 1.4 R15G 0 1 1 1.4 K23R 0 1 1 1.4 R24Q 1 0 1 1.4 F26V 0 1 1 1.4Y33S 1 0 1 1.4 I47T 0 1 1 1.4 R53H 0 1 1 1.4 L67R 1 0 1 1.4 Y69C/H^(§) 42 6 8.7 E74-P75-H76 > D 1 0 1 1.4 H76R 1 0 1 1.4 E77K 0 1 1 1.4N81K/Y^(§) 0 2 2 2.9 D83A/G/V^(§) 11 16 27 39.1 R114Q 0 1 1 1.4 S294Y 10 1 1.4 R307S 0 1 1 1.4 *369Y/E/G 3 0 3 4.3 Truncation 5 3 8 11.6 Anymutation 35 34 69 100.0 Total cases sequenced 261 292 Prevalence 13.41%11.64% ^(§)at least one representative mutation at this position hasbeen confirmed as a somatic mutation.

TABLE 9 All cSNVs detected in 10 DLBCL cell lines using RNA-seq data.Gene name Ensembl gene Mutation Effect (all isoforms) Cell Line HLA-CENSG00000204525 C > G W188S; W191S OCI-Ly19 AFF1 ENSG00000172493 C > TP866P OCI-Ly7 AQR ENSG00000021776 G > C A1013G DB ASCC3L1ENSG00000144028 T > C M387V OCI-Ly1 ASCC3L1 ENSG00000144028 T > C N313DOCI-Ly7 BCL2 ENSG00000171791 G > A N172N DB BCL2 ENSG00000171791 G > AL119L DB BCL2 ENSG00000171791 C > G R183R Karpas422 BCL2 ENSG00000171791G > A P59L Karpas422 BCL2 ENSG00000171791 C > T G47D Karpas422 BCL2ENSG00000171791 C > T R63R NU-DHL-1 BCL2 ENSG00000171791 C > T A2TNU-DHL-1 BCL2 ENSG00000171791 C > T L72L SU-DHL-6 BCL2 ENSG00000171791C > T P71P SU-DHL-6 BCL2 ENSG00000171791 T > A I48F SU-DHL-6 BCL2ENSG00000171791 T > G T69P WSU-DLCL2 BCL2 ENSG00000171791 C > G E13DWSU-DLCL2 BCL2 ENSG00000171791 G > A T187I OCI-Ly1 BCL2 ENSG00000171791G > A S161S OCI-Ly1 BCL2 ENSG00000171791 G > A A131V OCI-Ly1 BCL2ENSG00000171791 G > A S87S OCI-Ly1 BCL2 ENSG00000171791 C > T A85AOCI-Ly1 BCL2 ENSG00000171791 A > G F49L OCI-Ly1 BCL2 ENSG00000171791 A >G H20H OCI-Ly1 BCL2 ENSG00000171791 A > G D10D OCI-Ly1 BCL2ENSG00000171791 C > T G5G OCI-Ly1 BCL6 ENSG00000113916 G > T A587DOCI-Ly7 BCL6 ENSG00000113916 T > G N588H OCI-Ly19 BCL7A ENSG00000110987T > G M1R OCI-Ly1 BCL7A ENSG00000110987 C > T R29C OCI-Ly7 CARD11ENSG00000198286 C > T D223N; D230N; D247N Karpas422 CARS ENSG00000110619G > A H147H; H157H; H240H OCI-Ly7 CCND3 ENSG00000112576 G > A P234S;P280S; P284S NU-DHL-1 CCND3 ENSG00000112576 T > C T233A; T279A; T283AOCI-Ly7 CCND3 ENSG00000112576 C > G A239P; A285P; A289P OCI-Ly19 CENPPENSG00000188312 G > A R141H; R182H NU-DUL-1 CREBBP ENSG00000005339 C > AE1238*; E1268* Karpas422 CREBBP ENSG00000005339 G > A A436V NU-DHL-1CREBBP ENSG00000005339 G > A Q170*; Q238* NU-DHL-1 CSTF2TENSG00000177613 T > A L428F DOHH-2 DBN1 ENSG00000113758 C > T R226Q;R228Q DB DDX56 ENSG00000136271 G > A L14L WSU-DLCL2 EGLN1ENSG00000135766 T > G S166R OCI-Ly19 EZH2 ENSG00000106462 A > T Y602N;Y646N DB EZH2 ENSG00000106462 A > T Y602N; Y646N Karpas422 EZH2ENSG00000106462 A > T Y602N; Y646N SU-DHL-6 EZH2 ENSG00000106462 T > AY602F; Y646F WSU-DLCL2 EZH2 ENSG00000106462 A > T Y602N; Y646N OCI-Ly1FAT4 ENSG00000196159 C > A I1760I; I3462I Karpas422 FOXO1ENSG00000150907 T > C I10V OCI-Ly1 FOXO1 ENSG00000150907 T > A M1LOCI-Ly1 GCN1L1 ENSG00000089154 A > G L2229L OCI-Ly1 GNA13ENSG00000120063 G > C Y89* DOHH-2 GNA13 ENSG00000120063 T > G Y308SSU-DHL-6 GNA13 ENSG00000120063 A > G F245S WSU-DLCL2 GNA13ENSG00000120063 A > T L197Q OCI-Ly1 GNA13 ENSG00000120063 A > G I34TOCI-Ly1 GTF3C1 ENSG00000077235 C > T R403Q; R405Q OCI-Ly7 HNRNPA1ENSG00000135486 T > G G234G OCI-Ly19 IFNGR2 ENSG00000159128 A > C I77L;I156L; I175L OCI-Ly1 IKZF3 ENSG00000161405 T > C N73S; N160S DOHH-2IKZF3 ENSG00000161405 A > C L75R; L162R NU-DUL-1 LSP1 ENSG00000130592G > A R187H; R249H; R253H; R256H; R377H WSU-DLCL2 MAST1 ENSG00000105613G > A A74T DB MEF2B ENSG00000064489 T > A D83V DB MEF2C ENSG00000081189A > G Y69H DB MEF2C ENSG00000081189 T > G E14A OCI-Ly1 MEF2CENSG00000081189 T > G K5T OCI-Ly1 MKI67 ENSG00000148773 T > G K617N;K977N SU-DHL-6 MLL2 ENSG00000167548 C > A L3496L DB MLL2 ENSG00000167548G > A Q2156* DB MLL2 ENSG00000167548 G > A S4824F NU-DHL-1 MLL2ENSG00000167548 G > A R1323* OCI-Ly1 MLL2 ENSG00000167548 G > A Q3384*NU-DUL-1 MLL2 ENSG00000167548 C > A D635Y NU-DUL-1 NCKAP1LENSG00000123338 A > G V105V OCI-Ly19 PCDHGC5 ENSG00000081853 A > G L726LWSU-DLCL2 PLCG2 ENSG00000197943 C > T G426G OCI-Ly7 PRDM15ENSG00000141956 G > C L361V; L398V; L727V SU-DHL-6 PSAP ENSG00000197746A > T L260H WSU-DLCL2 RBM39 ENSG00000131051 A > G I240T; I247T; I397TOCI-Ly7 RFTN1 ENSG00000131378 T > A H83L OCI-Ly1 RFXDC2 ENSG00000181827C > T W685* NU-DUL-1 RNF14 ENSG00000013561 G > T Q133H; Q259H OCI-Ly1SMG6 ENSG00000070366 G > A R767C OCI-Ly1 SOS2 ENSG00000100485 T > CS271G Karpas422 SPTBN1 ENSG00000115306 C > A D1318E; D1331E; D1344E DBSTAT6 ENSG00000166888 T > C Q286R NU-DHL-1 STAT6 ENSG00000166888 C > GG375R OCI-Ly1 TNFAIP3 ENSG00000118503 G > A G367G DOHH-2 TP53ENSG00000141510 G > A R155W; R248W DB TP53 ENSG00000141510 T > A K319*Karpas422 TP53 ENSG00000141510 T > C Y141C; Y234C SU-DHL-6 TP53ENSG00000141510 A > C C83G; C176G OCI-Ly1 TP53 ENSG00000141510 C > TR65H; R158H OCI-Ly1 TP53 ENSG00000141510 C > T G152D; G245D OCI-Ly7 TP53ENSG00000141510 C > T V50M; V143M NU-DUL-1 TSEN54 ENSG00000182173 C > TR490W OCI-Ly1 TSEN54 ENSG00000182173 G > C G525A OCI-Ly1 USP34ENSG00000115464 T > A S1685S; S1837S SU-DHL-6 ZMYND8 ENSG00000101040 C >G V518L; V537L; V538L; V543L; V563L OCI-Ly7

CITATIONS FOR REFERENCES REFERRED TO IN THE SPECIFICATION

-   1. Anderson, J. R., Armitage, J. O. & Weisenburger, D. D.    Epidemiology of the non-Hodgkin“s lymphomas: distributions of the    major subtypes differ by geographic locations. Non-Hodgkin”s    Lymphoma Classification Project. Ann. Oncol. 9, 717-720 (1998).-   2. Lenz, G. & Staudt, L. M. Aggressive lymphomas. N Engl J Med 362,    1417-1429 (2010).-   3. Horsman, D. E. et al. Follicular lymphoma lacking the    t(14;18)(q32;q21): identification of two disease subtypes. Br J    Haematol 120, 424-433 (2003).-   4. Iqbal, J. et al. BCL2 translocation defines a unique tumor subset    within the germinal center B-cell-like diffuse large B-cell    lymphoma. Am J Pathol 165, 159-166 (2004).-   5. Lenz, G. et al. Molecular subtypes of diffuse large B-cell    lymphoma arise by distinct genetic pathways. Proc Natl Acad Sci USA    105, 13520-13525 (2008).-   6. Pasqualucci, L. et al. Inactivation of the PRDM1/BLIMP1 gene in    diffuse large B cell lymphoma. J Exp Med 203, 311-317 (2006).-   7. Kato, M. et al. Frequent inactivation of A20 in B-cell lymphomas.    Nature 459, 712-716 (2009).-   8. Compagno, M. et al. Mutations of multiple genes cause    deregulation of NF-kappaB in diffuse large B-cell lymphoma. Nature    459, 717-721 (2009).-   9. Davis, R. E. et al. Chronic active B-cell-receptor signalling in    diffuse large B-cell lymphoma. Nature 463, 88-92 (2010).-   10. Ngo, V. N. et al. Oncogenically active MYD88 mutations in human    lymphoma. Nature 470, 115-119 (2011).-   11. Mardis, E. R. et al. Recurring mutations found by sequencing an    acute myeloid leukemia genome. N Engl J Med 361, 1058-1066 (2009).-   12. Shah, S. P. et al. Mutational evolution in a lobular breast    tumour profiled at single nucleotide resolution. Nature 461, 809-813    (2009).-   13. Morin, R. D. et al. Somatic mutations altering EZH2 (Tyr641) in    follicular and diffuse large B-cell lymphomas of germinal-center    origin. Nat Genet 42, 181-185 (2010).-   14. Futreal, P. A. et al. A census of human cancer genes. Nat Rev    Cancer 4, 177-183 (2004).-   15. Pasqualucci, L. et al. Inactivating mutations of    acetyltransferase genes in B-cell lymphoma. Nature 471, 189-195    (2011).-   16. Yusuf, I., Zhu, X., Kharas, M. G., Chen, J. & Fruman, D. A.    Optimal B-cell proliferation requires phosphoinositide    3-kinase-dependent inactivation of FOXO transcription factors. Blood    104, 784-787 (2004).-   17. Saito, M. et al. BCL6 suppression of BCL2 via Miz1 and its    disruption in diffuse large B cell lymphoma. Proc Natl Acad Sci USA    106, 11294-11299 (2009).-   18. Lenz, G. et al. Oncogenic CARD11 mutations in human diffuse    large B cell lymphoma. Science 319, 1676-1679 (2008).-   19. Greenman, C., Wooster, R., Futreal, P. A., Stratton, M. R. &    Easton, D. F. Statistical analysis of pathogenicity of somatic    mutations in cancer. Genetics 173, 2187-2198 (2006).-   20. Cheung, K. J. et al. Acquired TNFRSF14 mutations in follicular    lymphoma are associated with worse prognosis. Cancer Res 70,    9166-9174 (2010).-   21. Du, M. Q. et al. BCL10 gene mutation in lymphoma. Blood 95,    3885-3890 (2000).-   22. Kreutz, B., Hajicek, N., Yau, D. M., Nakamura, S. & Kozasa, T.    Distinct regions of Galpha13 participate in its regulatory    interactions with RGS homology domain-containing RhoGEFs. Cell    Signal 19, 1681-1689 (2007).-   23. Bhattacharyya, R. & Wedegaertner, P. Galpha 13 requires    palmitoylation for plasma membrane localization, Rho-dependent    signaling, and promotion of p115-RhoGEF membrane binding. J Biol    Chem 275, 14992-14999 (2000).-   24. Manganello, J. M., Huang, J., Kozasa, T.,    Voyno-Yasenetskaya, T. A. & Le Breton, G. C. Protein kinase    A-mediated phosphorylation of the Galpha13 switch I region alters    the Galphabetagamma13-G protein-coupled receptor complex and    inhibits Rho activation. J Biol Chem 278, 124-130 (2003).-   25. Brunet, A. et al. Protein Kinase SGK Mediates Survival Signals    by Phosphorylating the Forkhead Transcription Factor FKHRL1    (FOXO3a). Mol Cell Biol 21, 952-965 (2001).-   26. Tai, D. J. C., Su, C., Ma, Y. & Lee, E. H. Y. SGK1    phosphorylation of IkappaB Kinase alpha and p300 Up-regulates    NF-kappaB activity and increases N-Methyl-D-aspartate receptor NR2A    and NR2B expression. J Biol Chem 284, 4073-4089 (2009).-   27. Mo, J. et al. Serum- and glucocorticoid-inducible kinase 1    (SGK1) controls Notch1 signaling by downregulation of protein    stability through Fbw7 ubiquitin ligase. J Cell Sci 124, 100-112    (2011).-   28. Young, K. H. et al. Structural profiles of TP53 gene mutations    predict clinical outcome in diffuse large B-cell lymphoma: an    international collaborative study. Blood 112, 3088-3098 (2008).-   29. Shilatifard, A. Molecular implementation and physiological roles    for histone H3 lysine 4 (H3K4) methylation. Current Opinion in Cell    Biology 20, 341-348 (2008).-   30. Milne, T. et al. MLL Targets SET Domain Methyltransferase    Activity to Hox Gene Promoters. Mol Cell 10, 1107-1117 (2002).-   31. Krumlauf, R. Hox genes in vertebrate development. Cell 78,    191-201 (1994).-   32. Canaani, E. et al. ALL-1//MLL1, a homologue of Drosophila    TRITHORAX, modifies chromatin and is directly involved in infant    acute leukaemia. Br J Cancer 90, 756-760 (2004).-   33. Wiedemann, L. et al. Global Analysis of H3K4 Methylation Defines    MLL Family Member Targets and Points to a Role for MLL1-Mediated    H3K4 Methylation in the Regulation of Transcriptional Initiation by    RNA Polymerase II. Mol Cell Biol 29, 6074-6085 (2009).-   34. Issaeva, I. et al. Knockdown of ALR (MLL2) Reveals ALR Target    Genes and Leads to Alterations in Cell Adhesion and Growth. Mol Cell    Biol 27, 1889-1903 (2007).-   35. Pleasance, E. D. et al. A small-cell lung cancer genome with    complex signatures of tobacco exposure. Nature 463, 184-190 (2010).-   36. Dalgliesh, G. L. et al. Systematic sequencing of renal carcinoma    reveals inactivation of histone modifying genes. Nature 463, 360-363    (2010).-   37. Parsons, D. W. et al. The Genetic Landscape of the Childhood    Cancer Medulloblastoma. Science 331, 435-439 (2011).-   38. Iqbal, J. et al. Distinctive patterns of BCL6 molecular    alterations and their functional consequences in different subgroups    of diffuse large B-cell lymphoma. Leukemia 21, 2332-2343 (2007).-   39. Pasini, D. et al. Characterization of an antagonistic switch    between histone H3 lysine 27 methylation and acetylation in the    transcriptional regulation of Polycomb group target genes. Nucleic    Acids Res (2010).doi:10.1093/nar/gkq244-   40. Giordano, A. & Avantaggiati, M. p300 and CBP: partners for life    and death. J Cell Physiol 181, 218-230 (1999).-   41. Han, A., He, J., Wu, Y., Liu, J. O. & Chen, L. Mechanism of    recruitment of class II histone deacetylases by myocyte enhancer    factor-2. J Mol Biol 345, 91-102 (2005).-   42. Youn, H. & Liu, J. Cabin1 represses MEF2-dependent Nur77    expression and T cell apoptosis by controlling association of    histone deacetylases and acetylases with MEF2. Immunity 13, 85-94    (2000).-   43. Yap, D. B. et al. Somatic mutations at EZH2 Y641 act dominantly    through a mechanism of selectively altered PRC2 catalytic activity,    to increase H3K27 trimethylation. Blood 117, 2451-2459 (2011).-   44. Sneeringer, C. J. et al. Coordinated activities of wild-type    plus mutant EZH2 drive tumor-associated hypertrimethylation of    lysine 27 on histone H3 (H3K27) in human B-cell lymphomas. Proc Natl    Acad Sci USA 107, 20980-20985 (2010).-   45. Li, H. & Durbin, R. Fast and accurate short read alignment with    Burrows-Wheeler transform. Bioinformatics 25, 1754-1760 (2009).-   46. Goya, R. et al. SNVMix: predicting single nucleotide variants    from next-generation sequencing of tumors. Bioinformatics 26,    730-736 (2010).-   47. Robertson, G. et al. De novo assembly and analysis of RNA-seq    data. Nat Meth 7, 909-912 (2010).-   48. Mortazavi, A., Williams, B. A., Mccue, K., Schaeffer, L. &    Wold, B. Mapping and quantifying mammalian transcriptomes by    RNA-Seq. Nat Meth 5, 621-628 (2008).-   49. Wright, G. et al. A gene expression-based method to diagnose    clinically distinct subgroups of diffuse large B cell lymphoma. Proc    Natl Acad Sci USA 100, 9991-9996 (2003).-   50. He, J. et al. Structure of p300 bound to MEF2 on DNA reveals a    mechanism of enhanceosome assembly. Nucleic Acids Res    (2011).doi:10.1093/nar/gkr030-   51. Beckwith, M., Longo, D. L., O'Connell, C. D., Moratz, C. M. &    Urba, W. J. Phorbol ester-induced, cell-cycle-specific, growth    inhibition of human B-lymphoma cell lines. J. Natl. Cancer Inst. 82,    501-509 (1990).-   52. Kluin-Nelemans, H. C., Limpens, J., Meerabux, J., Beverstock, G.    C., Jansen, J. H., et al. A new non-Hodgkin's B-cell line (DoHH2)    with a chromosomal translocation t(14;18)(q32;q21). Leukemia 5,    221-224 (1991).-   53. Dyer, M. J., Fischer, P., Nacheva, E., Labastide, W. &    Karpas, A. A new human B-cell non-Hodgkin's lymphoma cell line    (Karpas 422) exhibiting both t (14;18) and t(4;11) chromosomal    translocations. Blood 75, 709-714 (1990).-   54. Winter, J. N., Variakojis, D. & Epstein, A. L. Phenotypic    analysis of established diffuse histiocytic lymphoma cell lines    utilizing monoclonal antibodies and cytochemical techniques. Blood    63, 140-146 (1984).-   55. Epstein, A., Variakojis, D., Berger, C. & Hecht, B. Use of novel    chemical supplements in the establishment of three human malignant    lymphoma cell lines (NU-DHL-1, NUDUL-1, and NU-AMB-1) with    chromosome 14 translocations. International Journal of Cancer 35,    619-627 (1985).-   56. Al-Katib, A. M., Smith, M. R., Kamanda, W. S., Pettit, G. R.,    Hamdan, M., et al. Bryostatin 1 down-regulates mdr1 and potentiates    vincristine cytotoxicity in diffuse large cell lymphoma xenografts.    Clin Cancer Res 4, 1305-1314 (1998).-   57. Mehra, S., Messner, H., Minden, M. & Chaganti, R. S. K.    Molecular cytogenetic characterization of non-Hodgkin lymphoma cell    lines. Genes Chromosom. Cancer 33, 225-234 (2002).-   58. Levy, S., Sutton, G., Ng, P., Feuk, L., Halpern, A., et al. The    diploid genome sequence of an individual human. PLoS Biol 5,    e254-e254 (2007).-   59. Wheeler, D. A., Srinivasan, M., Egholm, M., Shen, Y., Chen, L.,    et al. The complete genome of an individual by massively parallel    DNA sequencing. Nature 452, 872-876 (2008).-   60. Wang, J., Wang, W., Li, R., Li, Y., Tian, G., et al. The diploid    genome sequence of an Asian individual. Nature 456, 60-65 (2008).-   61. Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G.    P., Milton, J., et al. Accurate whole human genome sequencing using    reversible terminator chemistry. Nature 456, 53-59 (2008).-   62. Robinson, J. T., Thorvaldsdóttir, H., Winckler, W., Guttman, M.,    Lander, E. S., et al. Integrative genomics viewer. Nat Biotechnol    29, 24-26 (2011).-   63. Robinson, M. D. & Oshlack, A. A scaling normalization method for    differential expression analysis of RNA-seq data. 1-9 (2010).-   64. Staden, R. The Staden sequence analysis package. Mol.    Biotechnol. 5, 233-241 (1996).-   65. Pasqualucci, L., Guglielmino, R., Malek, S. N., Novak, U.,    Compagno, M., et al. Aberrant Somatic Hypermutation Targets an    Extensive Set of Genes in Diffuse Large B-Cell Lymphoma. ASH Annual    Meeting Abstracts 104, 1528-1528 (2004).-   66. Pasqualucci, L., Neumeister, P., Goossens, T., Nanjangud, G.,    Chaganti, R., et al. Hypermutation of multiple proto-oncogenes in    B-cell diffuse large-cell lymphomas. Nature 412, 341-346 (2001).-   67. Pasqualucci, L., Migliazza, A., Basso, K., Houldsworth, J.,    Chaganti, R. S. K., et al. Mutations of the BCL6 proto-oncogene    disrupt its negative autoregulation in diffuse large B-cell    lymphoma. Blood 101, 2914-2923 (2003).-   68. Jones, S. J., Laskin, J., Li, Y. Y., Griffith, O. L., An, J., et    al. Evolution of an adenocarcinoma in response to selection by    targeted kinase inhibitors. Genome Biol 11, R82-R82 (2010).-   69. Krzywinski, M., Schein, J., Birol, I., Connors, J., Gascoyne,    R., et al. Circos: an information aesthetic for comparative    genomics. Genome Res 19, 1639-1645 (2009).-   70. Birol, I., Jackman, S., Nielsen, C., Qian, J., Varhol, R., et    al. De novo Transcriptome Assembly with ABySS. Bioinformatics    (2009).doi:btp367 [pii] 10.1093/bioinformatics/btp367-   71. Robertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y.,    et al. Genome-wide profiles of STAT1 DNA association using chromatin    immunoprecipitation and massively parallel sequencing. Nat Meth 4,    651-657 (2007).-   72. Wiegand, K. C., Shah, S. P., Al-Agha, O. M., Zhao, Y., Tse, K.,    et al. ARIDIA mutations in endometriosis-associated ovarian    carcinomas. N Engl J Med 363, 1532-1543 (2010).-   73. Gnirke, A., Melnikov, A., Maguire, J., Rogov, P., LeProust, E.,    et al. Solution hybrid selection with ultra-long oligonucleotides    for massively parallel targeted sequencing. Nat Biotechnol 27,    182-189 (2009).-   74. Chin, S., Daigo, Y., Huang, H., Iyer, N. G., Callagy, G., et al.    A simple and reliable pretreatment protocol facilitates fluorescent    in situ hybridisation on tissue microarrays of paraffin wax embedded    tumour samples. MP, Mol. Pathol. 56, 275-279 (2003).-   75. Liu, X. et al. The structural basis of protein acetylation by    the p300/CBP transcriptional coactivator. Nature 451, 846-850    (2008).-   76. Lewis, B. P., Green, R. E. & Brenner, S. E. Evidence for the    widespread coupling of alternative splicing and nonsense-mediated    mRNA decay in humans. Proc Natl Acad Sci USA 100, 189-192 (2003).-   77. Diehl, S. et al. STAT3-mediated up-regulation of BLIMP1 Is    coordinated with BCL6 down-regulation to control human plasma cell    differentiation. J Immunol 180, 4805-4815 (2008).-   78. Ariel, O., Levi, Y. & Hollander, N. Signal transduction by CD58:    The transmembrane isoform transmits signals outside lipid rafts    independently of the GPI-anchored isoform. Cell Signal 21, 1100-1108    (2009).-   79. Wilker, P. et al. Transcription factor Mef2c is required for B    cell proliferation and survival after antigen receptor stimulation.    Nat Immunol 9, 603-612 (2008).-   80. Youn, H., Sun, L., Prywes, R. & Liu, J. Apoptosis of T cells    mediated by Ca2+-induced release of the transcription factor MEF2.    Science 286, 790-793 (1999).-   81. Han, A. et al. Sequence-specific recruitment of transcriptional    co-repressor Cabin1 by myocyte enhancer factor-2. Nature 422,    730-734 (2003).-   82. Hunt, K. E., Hall, B. & Reichard, K. K. Translocations involving    MUM1 are rare in diffuse large B-cell lymphoma. Appl Immunohistochem    Mol Morphol 18, 109-112 (2010).-   83. Linehan, L. A., Warren, W. D., Thompson, P. A., Grusby, M. J. &    Berton, M. T. STAT6 is required for IL-4-induced germline Ig gene    transcription and switch recombination. J Immunol 161, 302-310    (1998).-   84. Saeki, K., Miura, Y., Aki, D., Kurosaki, T. & Yoshimura, A. The    B cell-specific major raft protein, Raftlin, is necessary for the    integrity of lipid raft and BCR signal transduction. EMBO J 22,    3015-3026 (2003).-   85. Peled, J. U. et al. Requirement for cyclin D3 in germinal center    formation and function. Cell Res 20, 631-646 (2010).-   86. Srinivasan, L. et al. PI3 kinase signals BCR-dependent mature B    cell survival. Cell 139, 573-586 (2009).-   87. Cortés, M. & Georgopoulos, K. Aiolos is required for the    generation of high affinity bone marrow plasma cells responsible for    long-term immunity. J Exp Med 199, 209-219 (2004).-   88. Shaffer, A. L. et al. Blimp-1 orchestrates plasma cell    differentiation by extinguishing the mature B cell gene expression    program. Immunity 17, 51-62 (2002).-   89. Minegishi, Y. et al. Dominant-negative mutations in the    DNA-binding domain of STAT3 cause hyper-IgE syndrome. Nature 448,    1058-1062 (2007).-   90. Mullighan, C. G. et al. CREBBP mutations in relapsed acute    lymphoblastic leukaemia. Nature 471, 235-239 (2011).-   91. Janknecht, R. The versatile functions of the transcriptional    coactivators p300 and CBP and their roles in disease. Histol.    Histopathol 17, 657-668 (2002).-   92. Potthoff, M. & Olson, E. MEF2: a central regulator of diverse    developmental programs. Development 134, 4131-4140 (2007).-   93. Youn, H. D., Chatila, T. A. & Liu, J. O. Integration of    calcineurin and MEF2 signals by the coactivator p300 during T-cell    apoptosis. EMBO J 19, 4323-4331 (2000).-   94. Wu, W. et al. Conservation and evolution in and among SRF- and    MEF2-type MADS domains and their binding sites. Molecular biology    and evolution (2010).doi:10.1093/molbev/msq214-   95. Martin, J. et al. A Mef2 gene that generates a muscle-specific    isoform via alternative mRNA splicing. Mol Cell Biol 14, 1647-1656    (1994).-   96. Molkentin, J. D., Black, B. L., Martin, J. F. & Olson, E. N.    Mutational analysis of the DNA binding, dimerization, and    transcriptional activation domains of MEF2C. Mol Cell Biol 16,    2627-2636 (1996).-   97. van der Heide, L. P. & Smidt, M. P. Regulation of FoxO activity    by CBP/p300-mediated acetylation. Trends Biochem. Sci. 30, 81-86    (2005).-   98. Dequiedt, F. et al. HDAC7, a thymus-specific class II histone    deacetylase, regulates Nur77 transcription and TCR-mediated    apoptosis. Immunity 18, 687-698 (2003).-   99. Eylenstein, A. et al. Stimulation of Ca2+-channel Orai1/STIM1 by    serum- and glucocorticoid-inducible kinase 1 (SGK1). FASEB J 25,    2012-2021 (2011).-   100. Dunleavy, K. et al. Differential efficacy of bortezomib plus    chemotherapy within molecular subtypes of diffuse large B-cell    lymphoma. Blood 113, 6069-76 (2009).-   101. Hernandez-Ilizaliturri, F. J. et al. Higher response to    lenalidomide in relapsed/refractory diffuse large B-cell lymphoma in    nongerminal center b-cell-like than in germinal center B-cell-like    phenotype. Cancer (2011)

1. A method of identifying a subject as having B-cell non-Hodgkinlymphoma (NHL), the method comprising testing a sample from the subjectfor a mutation in one or more biomarkers listed in Table 1, wherein thepresence of the mutation identifies the subject as having B-cell NHL. 2.The method of claim 1, wherein testing the sample comprises detectingone or more mutations in a nucleic acid coding for one or morebiomarkers listed in Table
 1. 3. The method of claim 1, wherein testingthe sample comprises detecting one or more mutations in a polypeptidecoding for one or more biomarkers listed in Table
 1. 4. The method ofclaim 1, wherein the sample is a tumour sample from a subject suspectedof having B-cell non-Hodgkin lymphoma.
 5. The method of claim 1, whereinthe mutation is a somatic mutation.
 6. The method of claim 1, whereinthe one or more biomarkers comprise a histone modifying gene.
 7. Themethod of claim 1, wherein the histone modifying gene is MLL2, MEF2B,CREBBP, EP300, EZH2 or H3K27.
 8. The method of claim 1, wherein the oneor more biomarkers are selected from FOXO1, CCND3, BTG2 and B2M.
 9. Themethod of claim 1, wherein the one or more biomarkers are selected fromEZH2, TNFRS14, CREBBP, BCL10, BTG1, GNA13, SGK1, MLL2 and MEF2B.
 10. Themethod of claim 9, wherein the one or more biomarkers are selected fromBTG1, GNA13, SGK1, MLL2 and MEF2B.
 11. The method of claim 1, whereinthe one or more biomarkers is CD79B or MYD88.
 12. The method of claim 1,wherein the mutation is listed in Table
 3. 13. The method of claim 1,wherein the biomarker is MLL2.
 14. The method of claim 13, wherein themutation is listed in Table
 6. 15. The method of claim 1, wherein thebiomarker is MEF2B.
 16. The method of claim 15, wherein the mutation islisted in Table
 7. 17. The method of claim 15, wherein the mutation isat amino acid position K4, Y69, N81 or D83 of a MEF2B polypeptide. 18.The method of claim 1, further comprising testing the sample formutations in BCL2 or TP53.
 19. The method of claim 1, comprising testingthe sample for a mutation in 2 or more, 3 or more, 4 or more, or 5 ormore biomarkers listed in Table
 1. 20. A method of classifying a subjectsuspected of having B-cell non-Hodgkin lymphoma (NHL) comprising testinga sample from the subject for a mutation in one or more biomarkersselected from MEF2B, SGK1, GNA13, and TNFRS14, wherein subjects thathave a mutation in the one or more biomarkers are classified as havinggerminal centre B-cell (GCB) diffuse large B cell lymphoma (DLBCL). 21.The method of claim 20, further comprising testing the sample for amutation in BCL2, TP53 or EZH2.
 22. A method of classifying a subjectsuspected of having B-cell non-Hodgkin lymphoma (NHL) comprising testinga sample from the subject for a mutation in MYD88 or CD79B, whereinsubjects that have a mutation in MYD88 or CD79B are classified as havingactivated B-cell (ABC) diffuse large B cell lymphoma (DLBCL).
 23. Themethod of claim 20, further comprising selecting a treatment for thesubject based on the classification of the sample as GCB DLBCL.
 24. Themethod of claim 23, wherein the sample is classified as GCB DLBCL andthe treatment that is selected comprises administration of a histonedeacetylase (HDAC) inhibitor-class drug.
 25. The method of claim 20,wherein the sample is a tumour sample.
 26. The method of claim 20,wherein the mutation is listed in Table 3, Table 6, or Table
 7. 27.-30.(canceled)